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Automatic Exploit Generation (AEG) involves automatically discovering paths in a program that trigger vulnerabilities, thereby generating exploits. While there is considerable research on heap-related vulnerability detection, such as detecting Heap Overflow and Use After Free (UAF) vulnerabilities, among contemporary heap-automated exploit techniques, only certain automated exploit techniques can hijack program control flow to the shellcode. An important limitation of this approach is that it cannot effectively bypass Linux’s protection mechanisms. To solve this problem, we introduced Automatic Advanced Heap Exploit Generation (AAHEG). It first applies symbolic execution to analyze heap-related primitives in files and then detects potential heap-related vulnerabilities without a source code. After identifying these vulnerabilities, AAHEG builds an exploit abstract syntax tree (AST) to identify one or more successful exploit strategies, such as fast bin attack and Safe-unlink. AAHEG then selects exploitable methods via an abstract syntax tree (AST) and performs final testing to produce the final exploit. AAHEG chose to generate advanced heap-related exploits because the exploits can bypass Linux protections. Basically, AAHEG can automatically detect heap-related vulnerabilities in binaries without source code, build an exploit AST, choose from a variety of advanced heap exploit methods, bypass all Linux protection mechanisms, and generate final file-form exploit based on pwntools which can pass local and remote testing. Experimental results show that AAHEG successfully completed vulnerability detection and exploit generation for 20 Capture The Flag (CTF) binary files, 11 of which have all protection mechanisms enabled.

Maize kernel growth is sensitive to heat stress, which is predicted to result in yield loss. However, the response of maize to short-term heat stress during different kernel-growth stages is still not clear. A 3-year field experiment, included two heat-stress treatments (LSH, lag-stage heat stress; FSH, effective-filling-stage heat stress), was conducted in 2019–2021. The results showed that LSH and FSH significantly reduced the grain yield by 8.7–14.9% and 11.6–17.6%, respectively, compared with the control (CK). LSH mainly reduced the kernel number per ear, and FSH mainly reduced the kernel weight. Heat stress reduced the SPAD and chlorophyll content during the effective-filling stage, but not in the lag stage. Photosynthesis was obviously reduced under heat stress during both stages; however, the photosynthesis rate during the lag stage was higher than during the effective-filling stage. The decreased amplitude of dry matter under LSH was higher than under FSH during the heating period. However, there was no difference between the CK and LSH samples in terms of dry-matter accumulation from the end of heat stress to harvest, which was significantly reduced under FSH. Additionally, decreased starch-synthesis-related enzyme activity, i.e., adenosine diphos-phoglucose pyrophosphprylase, contributed to the kernel number and kernel weight loss in LSH and FSH, respectively. The kernel-growth rate (per ear) was lowered, but the growth duration was not shortened in this study. Consequently, LSH mainly reduced the photosynthesis rate (Pn), resulting in kernel abortion and yield penalty. FSH mainly reduced the Pn and chlorophyll content, which reduced the kernel weight, and increased yield loss.

This study investigated the impact of a multiple epoxy chain extender (ADR) on the rheological behavior, crystallization, and mechanical properties of polyglycolic acid (PGA). Tests of the torque and melt mass flow rate and dynamic rheological analysis were conducted to study the rheological behavior of PGA modified with ADR. The rheological results of the modified PGA showed a significantly increased viscosity and storage modulus with an increase in the ADR amount, which could be attributed to the chain extension/branching reactions between PGA and ADR. It was proved that ADR could be used as an efficient chain extender for tailoring the rheological performance of PGA. The Han plot of the modified PGA showed a transition of viscous behavior to elastic behavior, while the ADR content was increased from 0 to 0.9 phr. The formation of long-chain branches (LCBs) was confirmed via the Cole–Cole plot and weighted relaxation spectrum, wherein the LCBs substantially changed the rheological behavior of the modified PGA. The vGP plots predicted a star-type topological structure for the LCBs. The results of non-isothermal crystallization kinetics suggested that the crystallization of the modified PGA was predominantly homogeneous nucleation and three-dimensional growth. The crystallinity decreased slightly with the increase in the ADR amount. Compared to neat PGA, the modified PGA samples exhibited better tensile and flexural performances.

Ship detection in synthetic aperture radar (SAR) images has attracted widespread attention due to its significance and challenges. In recent years, numerous detectors based on deep learning have achieved good performance in the field of SAR ship detection. However, ship targets of the same type always have various representations in SAR images under different imaging conditions, while different types of ships may have a high degree of similarity, which considerably complicates SAR target recognition. Meanwhile, the ship target in the SAR image is also obscured by background and noise. To address these issues, this paper proposes a novel oriented ship detection method in SAR images named SPG-OSD. First, we propose an oriented two-stage detection module based on the scattering characteristics. Second, to reduce false alarms and missing ships, we improve the performance of the network by incorporating SAR scattering characteristics in the first stage of the detector. A scattering-point-guided region proposal network (RPN) is designed to predict possible key scattering points and make the regression and classification stages of RPN increase attention to the vicinity of key scattering points and reduce attention to background and noise. Third, supervised contrastive learning is introduced to alleviate the problem of minute discrepancies among SAR object classes. Region-of-Interest (RoI) contrastive loss is proposed to enhance inter-class distinction and diminish intra-class variance. Extensive experiments are conducted on the SAR ship detection dataset from the Gaofen-3 satellite, and the experimental results demonstrate the effectiveness of SPG-OSD and show that our method achieves state-of-the-art performance.

The Programmable Logic Controller (PLC) is located at the junction of the virtual network and physical reality in the Industrial Control System (ICS), which is vulnerable to attacks due to its weak security. Specifically, firmware tampering attacks take the firmware under the PLC operating system as the primary attack target. The firmware provides the bridge between PLC’s hardware and software, which means tampering against the firmware can be more destructive and harmful than other attacks. However, existing defense and forensics methods against firmware tampering attacks are asymmetrical, which directly leads to the proliferation of such attacks and the difficulty of forensic tracing. How to accurately, quickly, and efficiently conduct forensics for such attacks is an urgent problem. In this paper, we designed and implemented a reliable detection method based on Joint Test Action Group (JTAG) and memory comparison—Aye, which can detect mainstream firmware tampering attacks reliably. To determine the effectiveness and reliability of Aye, we selected a widely used PLC to observe Aye’s performance in defense and forensics by simulating the two latest PLC firmware tampering attack methods. The experimental results show that Aye can effectively defend against firmware tampering attacks, helping improve the efficiency and accuracy of such attack detection and forensics.

Medicinal plants produce important substrates for their adaptation and defenses against environmental factors and, at the same time, are used for traditional medicine and industrial additives. Plants have relatively little in the way of secondary metabolites via biosynthesis. Recently, the whole-genome sequencing of medicinal plants and the identification of secondary metabolite production were revolutionized by the rapid development and cheap cost of sequencing technology. Advances in functional genomics, such as transcriptomics, proteomics, and metabolomics, pave the way for discoveries in secondary metabolites and related key genes. The multi-omics approaches can offer tremendous insight into the variety, distribution, and development of biosynthetic gene clusters (BGCs). Although many reviews have reported on the plant and medicinal plant genome, chemistry, and pharmacology, there is no review giving a comprehensive report about the medicinal plant genome and multi-omics approaches to study the biosynthesis pathway of secondary metabolites. Here, we introduce the medicinal plant genome and the application of multi-omics tools for identifying genes related to the biosynthesis pathway of secondary metabolites. Moreover, we explore comparative genomics and polyploidy for gene family analysis in medicinal plants. This study promotes medicinal plant genomics, which contributes to the biosynthesis and screening of plant substrates and plant-based drugs and prompts the research efficiency of traditional medicine.

The COVID-19 pandemic poses a threat to global health. Due to its high sensitivity, specificity, and stability, real-time fluorescence quantitative (real-time PCR) detection has become the most extensively used approach for diagnosing SARS-CoV-2 pneumonia. According to a report from the World Health Organization, emerging and underdeveloped nations lack nucleic acid detection kits and polymerase chain reaction (PCR) instruments for molecular biological detection. In addition, sending samples to a laboratory for testing may result in considerable delays between sampling and diagnosis, which is not favorable to the timely prevention and control of new crown outbreaks. Concurrently, there is an urgent demand for accurate PCR devices that do not require a laboratory setting, are more portable, and are capable of completing testing on-site. Hence, we report on HDLRT-qPCR, a new, low-cost, multiplexed real-time fluorescence detection apparatus that we have developed for on-site testing investigations of diverse diseases in developing nations. This apparatus can complete on-site testing rapidly and sensitively. The entire cost of this instrument does not exceed USD 760. In order to demonstrate the applicability of our PCR instrument, we conducted testing that revealed that we achieved gradient amplification and melting curves comparable to those of commercially available equipment. Good consistency characterized the testing outcomes. The successful detection of target genes demonstrates the reliability of our inexpensive PCR diagnostic technique. With this apparatus, there is no need to transport samples to a central laboratory; instead, we conduct testing at the sampling site. This saves time on transportation, substantially accelerates overall testing speed, and provides results within 40 min.

The Industrial Control System (ICS) is a public facility that provides services to lots of users; thus, its security has always been a critical factor in measuring its availability. Recently, a new type of attack on ICS has occurred frequently, which realizes the extortion of users by invading the information domain and destroying the physical domain. However, due to the diversity and unavailability of an ICS control logic, the targets of such attacks are usually limited to PCs and servers, leaving more disruptive attack methods unexplored. To contribute more possible attack methods to strengthen the immunity of ICS, in this paper, we propose a novel ransomware attack method named Industrial Control System Automatic Ransomware Constructor (ICS-ARC). Compared to existing ICS ransomware, ICS-ARC can automatically generate an International Electrotechnical Commission (IEC) compliant payload to compromise the Programmable Logic Controller (PLC) without a pre-known control logic, dramatically reducing adversary requirements and leaving room for error. To evaluate the attack capability of ICS-ARC, we built a tap water treatment system as the simulation experiment target for verification. The experimental results determine that ICS-ARC can automatically generate malicious code without the control logic and complete the attack against target PLCs. In addition, to assist the related research on future attacks and defenses, we present the statistical results and corresponding analysis of PLC based on Shodan.

The potential of soft-shelled turtle peptides (STP) against fatigue was evaluated. Mice orally supplemented with STP significantly increased the swimming time until tiredness by 35.4–57.1%. Although not statistically significant, STP increased muscle and thymus mass. In addition, the serum lactate, ammonia, blood urea nitrogen content and creatine kinase activity in STP-fed mice were dramatically decreased when compared to the control group. Furthermore, STP supplementation increased the reserves of liver glycogen and muscle glycogen, thus improved the energy metabolism system of mice. STP treatment contributed to increased superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities as well as a decrease in malondialdehyde (MDA), indicating an improvement in oxidative stress protection. The Western blot (WB) results indicated that the STP supplement effectively altered the expression of oxidative stress-related protein by modulating the NRF2/KEAP1 pathway. In summary, STP affected NRF2/KEAP1 levels in skeletal muscle, leading to antioxidant activity and a slower time to exhaustion during exercise.

In order to better control the vibration of the rotor system so as to improve the stability and safety of the rotor, a novel vibration control solution is needed. In this paper, the multi-objective optimization problem is used for designing a novel integral squeeze film bearing damper (ISFBD). The method attempts to reduce the stiffness and stress convergence of ISFBD, which can greatly decrease the transmitted force of the rotor system and better use the damping effect to dissipate the vibration energy. The finite element model of ISFBD is established to analyze the stiffness and stress, and the correctness of the calculation is verified by setting up a stiffness test platform. The sensitivity of different structural parameters of stiffness and stress is analyzed by ANOVA. Meanwhile, the non-dominated sorting genetic algorithm (NSGA-II) and grey correlation analysis (GRA) algorithms are coupled for multi-objective optimization of stiffness and stress. The results indicate that optimized ISFBD can distribute 26.6% of the rotor system’s energy and reduce 59.3% of the transmitted force at the bearing location. It is also proved that the optimization strategy is effective, which can provide a useful method for ISFBD design in practical applications.

Glycerol is a readily available and inexpensive substance that is mostly generated during biofuel production processes. In order to ensure the viability of the biofuel industry, it is essential to develop complementing technologies for the resource utilization of glycerol. Ethylene glycol is a two-carbon organic chemical with multiple applications and a huge market. In this study, an artificial enzymatic cascade comprised alditol oxidase, catalase, glyoxylate/hydroxypyruvate reductase, pyruvate decarboxylase and lactaldehyde:propanediol oxidoreductase was developed for the production of ethylene glycol from glycerol. The reduced nicotinamide adenine dinucleotide (NADH) generated during the dehydrogenation of the glycerol oxidation product d-glycerate can be as the reductant to support the ethylene glycol production. Using this in vitro synthetic system with self-sufficient NADH recycling, 7.64 ± 0.15 mM ethylene glycol was produced from 10 mM glycerol in 10 h, with a high yield of 0.515 ± 0.1 g/g. The in vitro enzymatic cascade is not only a promising alternative for the generation of ethylene glycol but also a successful example of the value-added utilization of glycerol.

As the population ages globally, there seem to be more people with Alzheimer’s disease. Unfortunately, there is currently no specific treatment for the disease. At present, Huperzine A (HupA) is one of the best drugs used for the treatment of Alzheimer’s disease and has been used in clinical trials for several years in China. HupA was first separated from Huperzia serrata, a traditional medicinal herb that is used to cure fever, contusions, strains, hematuria, schizophrenia, and snakebite for several hundreds of years in China, and has been confirmed to have acetylcholinesterase inhibitory activity. With the very slow growth of H. serrata, resources are becoming too scarce to meet the need for clinical treatment. Some endophytic fungal strains that produce HupA were isolated from H. serrate in previous studies. In this article, the diversity of the endophytic fungal community within H. serrata was observed and the relevance to the production of HupA by the host plant was further analyzed. A total of 1167 strains were obtained from the leaves of H. serrata followed by the stems (1045) and roots (824). The richness as well as diversity of endophytic fungi within the leaf and stem were higher than in the root. The endophytic fungal community was similar within stems as well as in leaves at all taxonomic levels. The 11 genera (Derxomyces, Lophiostoma, Cyphellophora, Devriesia, Serendipita, Kurtzmanomyces, Mycosphaerella, Conoideocrella, Brevicellicium, Piskurozyma, and Trichomerium) were positively correlated with HupA content. The correlation index of Derxomyces with HupA contents displayed the highest value (CI = 0.92), whereas Trichomerium showed the lowest value (CI = 0.02). Through electrospray ionization mass spectrometry (ESI-MS), it was confirmed that the HS7-1 strain could produce HupA and the total alkaloid concentration was 3.7 ug/g. This study will enable us to screen and isolate the strain that can produce HupA and to figure out the correlation between endophytic fungal diversity with HupA content in different plant organs. This can provide new insights into the screening of strains that can produce HupA more effectively.

Polyglycolic acid (PGA) is used as a reinforcing component to enhance the mechanical properties of poly(ethylene glycol-co-cyclohexane-1,4-dimethanol terephthalate) (PETG). The tensile performance, micromorphology, crystallinity, heat resistance, and melt mass flow rates (MFRs) of PETG/PGA blends with varying PGA contents were studied. Both the tensile yield strength and tensile modulus of the PETG/PGA blends increased gradually with an increase in the PGA content from 0 to 35 wt%. The tensile yield strength of the PETG/PGA (65/35) blend increased by 8.7% (44.38 to 48.24 MPa), and the tensile modulus increased by 40.2% (1076 to 1509 MPa). However, its tensile ductility decreased drastically, owing to the poor interfacial compatibility of PETG/PGA and the oversized PGA domains. A multiple epoxy chain extender (ADR) was introduced into the PETG/PGA (65/35) blend to improve its interfacial compatibility and rheological properties. The tensile performance, micromorphology, rheological properties, crystallinity, and heat resistance of PETG/PGA (65/35) blends with varying ADR contents were studied. The strong chain extension effect of ADR along with its reactive compatibilization improved the rheological properties and tensile ductility. By carefully controlling the ADR concentration, the performance of PETG/PGA blends can be regulated for different applications.

In this paper, vibration control of an unbalanced single-side cantilevered rotor system using a novel integral squeeze film bearing damper in terms of stability, energy distribution, and vibration control is analyzed. A finite element model of such a system with an integral squeeze film bearing damper (ISFBD) is developed. The stability, energy distribution, and vibration control of the unbalanced single-side cantilevered rotor system are calculated and analyzed based on the finite element model. The stiffness of the integral squeeze film bearing damper is designed using theoretical calculation and finite element model (FEM) simulation. The influence of installation position and quantity of integral squeeze film bearing dampers on the vibration control of the unbalanced cantilevered rotor system is discussed. An experimental platform is developed to validate the vibration control effect. The results show that the installation position and quantity of the integral squeeze film bearing dampers have different effects on the stability, energy distribution, and vibration control of the unbalanced cantilevered rotor system. When ISFBDs are installed at both bearing housings, the vibration control is best, and the vibration components of the time and frequency domains have good vibration control effects in four working conditions.