Current Chinese Science - Volume 2, Issue 6, 2022

Aims: This work investigates the photoluminescence properties of poly(3- octylthiophene), namely P3OT films, under excitation power and time light expositions. When exposed to monochromatic illumination, the degradation mechanism of P3OT films is precise in environmental conditions. However, in some environmental controlled or non-environmental conditions, the quenching luminescence of P3OT subject to monochromatic light excitation is not fully understood. In this context, it is necessary to understand what causes quenching luminescence of P3OT films under environmental conditions. Methods: The P3OT was synthesized by chronocoulometry, using tetraethylammonium tetrafluoroborate and lithium perchlorate as supporting electrolytes, and after it is deposited on a conductive substrate of fluoride-doped tin oxide (FTO). The films were synthesized and maintained under an argon atmosphere, and their thickness is dependent on the charge. The characterisation was achieved by applying techniques like UV-Vis absorption spectroscopy, photoluminescence, and emission ellipsometry. Results: The UV-Vis absorption measurements demonstrated a different interaction of polymer/ dopant due to the polaronic band. The results showed that photoluminescence quenching with time is a behaviour caused by energy transfer between quinone chains and pristine chains of the P3OT. The polarised emission measurements corroborate the hypothesis of energy transfer between chains. The emission ellipsometry technique was used to understand energy transfer processes and other properties. The self-absorption phenomenon and integrated PL investigation of the P3OT emission elucidated the mechanism involved in the observed properties. Conclusion: Besides that, the results show that photoluminescence quenching happens in nonenvironmental and environmental conditions, corroborating the hypothesis that PL quenching occurs because self-absorption phenomena influence the energy transfer mechanism.

Viral infections have constituted a serious menace to global health. The emergence of resistant strains resulting from adaptive evolution poses a great challenge to virus control. Heat Shock Protein 90 (Hsp90) can shepherd virus-mutated proteins to fold into functional conformations. Therefore, inhibiting Hsp90 can block the evolution of viruses. However, none of the current Hsp90 inhibitors has been approved because of the unacceptable side effects. Considering the importance of co-chaperones for Hsp90 conformational cycle, inhibiting Hsp90 through cochaperones may be a safe and effective strategy. Some natural agents can bind the co-chaperones to indirectly modulate Hsp90 activity with low toxicity. Besides, some of these natural agents indicate antiviral effects. Therefore, natural products are highly expected to be used as virus resistance preventives by targeting the co-chaperones of Hsp90.

Background: Face recognition belonging to biometric recognition has great application value. Its algorithm based on deep learning has been widely used in recent years. Meanwhile, problems that endanger social privacy and security gradually appear, such as stealing, abusing, and illegal deploying models. Objective: The objective of this study is to use chaos to construct a watermark trigger set for protecting the model's intellectual property rights, thereby enabling the model to resist fine-tuning and overwriting attacks. When the model is leaked, it can be traced through a special watermark. Methods: We used the unpredictability and initial value sensitivity of chaos to make the watermark imperceptible and endow multiple deep learning based face recognition models with special watermarks. Results: The face recognition deep learning model embedded watermarks successfully while having high precision for watermark extraction. Meanwhile, it maintained the original function as well as features of watermarks. Experimental results and theoretical analysis indicate that the proposed scheme can resist fine-tuning, overwriting attacks, and trace leaked models. Conclusion: The proposed scheme improved the model's fidelity, safety, practicality, completeness, effectiveness, and the ability to resist common attacks based on machine learning. With the help of special watermarks, related departments can effectively manage face recognition based on deep learning models.

Background: Although many scholars have argued that the key factor for success in the e-commerce is the deployment of a trusted and reliable process for the buyer, the meaning of customer trust in e-commerce and the factors affecting it are not still well-known and to be investigated. Understanding how customers build their trust and developing a trust model is beneficial to increase the ability to do so. Objective: The aim of this study was to investigate whether the factors such as cognitive and affective trust can affect customer behavior in online shopping or not. Methods: Questionnaire was used to collect data and to check their normality, and the Kolmogorov– Smirnov test was applied. Cronbach’s alpha was employed to test the reliability, and the Structural Equation Model (SEM) was utilized to confirm or reject the hypotheses. Inferential statistical analysis was performed using SmartPLS software. Results: While perceived website quality can affect cognitive trust, variables like security and privacies policy, and shared value of a website can influence affective trust. In addition, there are variables like prior-interaction experience, and perceived reputation of an e-tail which can impact on both cognitive and affective trust. On the other hand, it was shown that both cognitive and affective trust can influence customer satisfaction; a variable which along with internet usage experience, and online shopping experience affect loyalty intention. Conclusion: The empirical results show that cognitive and affective trust are prominent variables in online retailing. They mediate between PWQ, SPP, PIE, PETR, and SV on the one hand and CS on the other hand. In addition, CS influences LI. The same is true for OSE and IE.

Background: In situ soil properties exhibit inherent spatial variability, which is often described by a 3D random field. Soil properties at particular portions are available by site investigation. Wider site investigation scope provides a more accurate description of the geologic profile. However, limited by budget, choosing an effective site exploration scope is of significance. Objective: This study introduces a framework to determine the optimal site investigation strategy in the 3D domain, which yields the lowest mean risk of slope designs. Methods: The mean risk of slope designs is considered to be a function of the costs of site investigation, under-design, and over-design. The unconditional random fields are generated by the spectral representation method initially. Subsequently, the sampled data are incorporated into the random fields via the Kriging algorithm, and the conditional random fields are simulated. A 3D undrained slope is evaluated for illustration. Results: The effects of sampling locations and spacing on the risk of slope designs are examined. The results indicate that the optimal sampling location is close to the zone where slope failure may occur. Moreover, there exists an optimal sampling spacing that minimizes the mean risk of slope designs. Conclusion: This investigation can provide guidance for determining the optimal site exploration programs on the 3D domain with knowledge of the associated risks.

In recent years, flexible all-solid-state supercapacitors have been widely used as the energy storage device for various smart and wearable electronic devices. However, the design and fabrication of high-performance flexible supercapacitor electrodes are still challenging since most of the active materials used for supercapacitor electrodes lack the ability to form flexible and mechanically stable structures. Recently, cellulose nanomaterials (mainly including cellulose nanocrystals and cellulose nanofibrils) have gained extensive interest due to their large specific surface areas, versatile surface chemistry, high mechanical strength, and the ability to form mechanically stable structures (e.g., films, aerogels). These days, the design of flexible supercapacitor electrodes by combining cellulose nanomaterials with different active materials gradually attracted the attention of scholars. The main objective of this review is to give an overview of recent developments in the preparation of cellulose nanomaterials based flexible all-solid-state supercapacitor electrodes. The fabrication approach, structural characterization, and electrochemical performance of the invented cellulose nanomaterials based flexible supercapacitor are elaborated. Also, the current challenges and future outlook for the design and fabrication of cellulose nanomaterials based flexible all-solid-state supercapacitor are proposed.

Introduction: The current-voltage (I-V) characteristics of the Al/p-type Si Metal- Semiconductor (MS) and Al/GO/p-type Si Metal-Oxide-Semiconductor (MOS) structure were investigated at room temperature (300 K). Methods: The main electrical characteristics such as ideality factor (n), zero-bias barrier height (Φbo), and Series Resistance (RS) of Al/p-Si and Al/GO/p-type Si semiconductor structures were obtained from different methods using I-V measurements. Results: Experimental results show that the electrical properties obtained from Al/GO/p-type Si structure are I-V measurements generally slightly greater than those obtained from Al/p-type Si structure. Conclusion: However, the interface state densities resistance values obtained from the Al/GO/p-Si structure are generally slightly smaller than those obtained from Al/p-type Si structure. The interface states (NSS) as energy distribution functions (ESS-EV) were obtained by using I-V measurements for both Al/p-type Si and Al/GO/p-type Si structures.

Background: The existence of cloud pixels reduces the practicability of optical satellite remote sensing data. Existing cloud reconstruction methods generally cannot solve the following problems: (1) Large-scale thick clouds cannot be well reconstructed. (2) There are high requirements for reconstructed data. (3) Most data used to reconstruct are single temporal images. Methods: To overcome these problems, a new multi-temporal weighted aggregation method is proposed. Specifically, we adopt a multi-temporal iterative aggregation method for cloud pixels to reconstruct and a multi-temporal weighted aggregation method for cloud shadow pixels to reconstruct. Results: Finally, the experiment proves that our method can quickly and accurately complete the cloud reconstruction, and under the effective uniform color strategy, a cloud- free image with accurate geometric position and uniform gray scale can be obtained. Conclusion: Experiments prove that the pixel reconstruction method proposed in this paper has achieved good cloud and cloud shadow pixel reconstruction effects in different types of ground objects.