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Abstract In prior investigations, a correlation was established between patient outcomes in locally advanced non-small cell lung cancer (LA-NSCLC) following thoracic irradiation and parameters, such as pre/post-treatment neutrophil-to-lymphocyte ratio (NLR) and NLR change (ΔNLR). However, these parameters could potentially be influenced by radiation-related variables, such as gross tumor volume (GTV). The primary aim of this study was to elucidate the factors impacting post-treatment NLR and ΔNLR and to further assess their prognostic relevance. In this retrospective study, a cohort of 188 LA-NSCLC patients who underwent thoracic radiation between 2012 and 2017 was assessed. The calculation of pre/post-treatment NLR involved the use of absolute neutrophil and lymphocyte counts. ΔNLR was defined as the difference between post- and pre-treatment NLR values. To assess the relationships between various variables and overall survival (OS), local progression-free survival (LPFS), and distant metastasis-free survival (DMFS), the Kaplan–Meier technique and Cox proportional hazards regression were employed. Additionally, Spearman’s rank correlation analysis was carried out to investigate correlations between the variables. The analysis revealed that both post-treatment NLR (r = 0.315, P 67.41 cm3 group (P = 0.028 and P = 0.042, respectively), highlighting ΔNLR as the sole independent predictive factor for survival and metastasis, irrespective of GTV.

BackgroundEvery hospital manager aims to build harmonious, mutually beneficial, and steady-state departments. Therefore, it is important to explore a hospital department development assessment model based on objective hospital data. ObjectiveThis study aims to use a novel machine learning algorithm to identify key evaluation indexes for hospital departments, offering insights for strategic planning and resource allocation in hospital management. MethodsData related to the development of a hospital department over the past 3 years were extracted from various hospital information systems. The resulting data set was mined using neural machine algorithms to assess the possible role of hospital departments in the development of a hospital. A questionnaire was used to consult senior experts familiar with the hospital to assess the actual work in each hospital department and the impact of each department’s development on overall hospital discipline. We used the results from this questionnaire to verify the accuracy of the departmental risk scores calculated by the machine learning algorithm. ResultsDeep machine learning was performed and modeled on the hospital system training data set. The model successfully leveraged the hospital’s training data set to learn, predict, and evaluate the working and development of hospital departments. A comparison of the questionnaire results with the risk ranking set from the departments machine learning algorithm using the cosine similarity algorithm and Pearson correlation analysis showed a good match. This indicates that the department development assessment model and risk score based on the objective data of hospital systems are relatively accurate and objective. ConclusionsThis study demonstrated that our machine learning algorithm provides an accurate and objective assessment model for hospital department development. The strong alignment of the model's risk assessments with expert opinions, validated through statistical analysis, highlights its reliability and potential to guide strategic hospital management decisions.

Abstract Osteosarcoma (OS) is the most common malignant bone tumor with high pathological heterogeneity. Our study aimed to investigate disulfidptosis-related modification patterns in OS and their relationship with survival outcomes in patients with OS. We analyzed the single-cell-level expression profiles of disulfidptosis-related genes (DSRGs) in both OS microenvironment and OS subclusters, and HMGB1 was found to be crucial for intercellular regulation of OS disulfidptosis. Next, we explored the molecular clusters of OS based on DSRGs and related immune cell infiltration using transcriptome data. Subsequently, the hub genes of disulfidptosis in OS were screened by applying multiple machine models. In vitro and patient experiments validated our results. Three main disulfidptosis-related molecular clusters were defined in OS, and immune infiltration analysis suggested high immune heterogeneity between distinct clusters. The in vitro experiment confirmed decreased cell viability of OS after ACTB silencing and higher expression of ACTB in patients with lower immune scores. Our study systematically revealed the underlying relationship between disulfidptosis and OS at the single-cell level, identified disulfidptosis-related subtypes, and revealed the potential role of ACTB expression in OS disulfidptosis.

Abstract Background Ovarian cancer (OC) is the most lethal gynecologic malignant tumour. The mechanism promoting OC initiation and progression remains unclear. SET domain bifurcated histone lysine methyltransferase 1(SETDB1) acts as an oncogene in a variety of tumours. This study aims to explore the role of SETDB1 in OC. Methods GEO, TCGA, CSIOVDB and CPTAC databases jointly analysed SETDB1 mRNA and protein expression. Effect of SETDB1 expression on the clinical prognosis of OC patients was analysed through online Kaplan‒Meier plotter and CSIOVDB database. Then, the effect of SETDB1 in OC cells progression and mobility was examined using MTT, EdU, colony formation and transwell assay. Additionally, Cistrome DB database was used to visualize the binding of SETDB1 protein and splicing factor 3b subunit 4 (SF3B4) promoter, and dual-luciferase reporter gene assay was performed to confirm the interaction. Finally, bioinformatics analysis was employed to reveal the relationship between SETDB1 and the microenvironment of OC. Results In the present study, we found that SETDB1 was obviously upregulated in OC and its overexpression predicted poor prognosis of OC patients. Then, we verified that SETDB1 promoted the progression and motility of OC cells in vitro. Knockdown of SETDB1 had the opposite effect. Further research showed that SETDB1 acted as a transcription factor to activate SF3B4 expression. SF3B4 knockdown impaired the effect of SETDB1 to promote the proliferative capacity and motility of OC cells. Finally, the results of bioinformatics analysis confirmed that SETDB1 regulated the immune microenvironment of ovarian cancer. Conclusion SETDB1 promoted ovarian cancer progression by upregulating the expression of SF3B4 and inhibiting the tumour immunity. SETDB1 may be a promising prognostic and therapeutic marker for OC.

Abstract Private universities play an important role in many countries worldwide. Approximately one-third of university students worldwide are enrolled in private universities. In countries with a large proportion of private universities, the quality of private universities determines the quality of higher education in the country as a whole. In some developed countries, the quality is high; however, in most developing countries, the quality of private universities is significantly lower than that of public universities. In many countries, private universities are managed in either a “not-for-profit” or a “for-profit” manner. The management type of private universities that best supports high-quality development has become an important issue in the field of higher education in many developing countries, but there are only a few related quantitative studies. Taking one private university in China as an example, this study aims to reveal the path that best supports high-quality development for a private university regarding the choice between the not-for-profit and for-profit orientations. Based on a literature review, a system dynamics model of development for private universities is developed, and the case data are simulated and analyzed based on the model. It is concluded that the rapid development path with a not-for-profit orientation, which enjoys government financial allocation, is more conducive to the high-quality development of private universities. Finally, the study proposes the strategies of encouraging private universities to choose the not-for-profit orientation, increasing government investment in not-for-profit private universities, and strengthening the financial supervision of not-for-profit private universities to promote their high-quality development.

ObjectivesThis study aimed to construct a radiomics nomogram and validate its performance in the preoperative differentiation between early-stage (I and II) serous borderline ovarian tumors (SBOTs) and serous malignant ovarian tumors (SMOTs).MethodsData were collected from 80 patients with early-stage SBOTs and 102 with early-stage SMOTs (training set: n = 127; validation set: n = 55). Univariate and multivariate analyses were performed to identify the independent clinicoradiological factors. A radiomics signature model was constructed using radiomics features extracted from multidetector computed tomography images of the venous phase, in which the least absolute shrinkage and selection operator regression was employed to lessen the dimensionality of the data and choose the radiomics features. A nomogram model was established by combining independent clinicoradiological factors with the radiomics signature. The performance of nomogram calibration, discrimination, and clinical usefulness was evaluated using training and validation sets.ResultsIn terms of clinicoradiological characteristics, age (p = 0.001), the diameter of the solid component (p = 0.009), and human epididymis protein 4 level (p < 0.001) were identified as the independent risk factors of SMOT, for which the area under the curves (AUCs) were calculated to be 0.850 and 0.836 in the training and validation sets, respectively. Nine features were finally selected to construct the radiomics signature model, which exhibited AUCs of 0.879 and 0.826 for the training and validation sets, respectively. The nomogram model demonstrated considerable calibration and discrimination with AUCs of 0.940 and 0.909 for the training and validation sets, respectively. The nomogram model displayed more prominent clinical usefulness than the clinicoradiological and radiomics signature models according to the decision curve analysis.ConclusionsThe nomogram model can be employed as an individualized preoperative non-invasive tool for differentiating early-stage SBOTs from SMOTs.

The mechanical properties and toughness of phase change materials are often weakened by defects which affect the application of matrix in tribology, and considering the hybridization of nanomaterials is able to increase the upper limit of materials’ performance. In this study, the in-situ polymerization of isopropylacrylamide was used on the surface of graphene and MXene to prepare a phase change two-dimensional composite with reversible phase change under specific temperatures. The composites were dispersed in epoxy resin matrix by KH550 (γ-Aminopropyl triethoxysilane) to realize phase change modulation of tribological properties. The results showed that the tribological properties of the modified epoxy resin coating realized friction reduction and anti-wear functions, and exhibited different tribological properties at different temperatures. The friction coefficient and wear rate of the composite coatings can be reduced to 0.1 % and 82.2 %, respectively, which is mainly attributed to the two-dimensional structure and physical characteristics of graphene and MXene, as well as the mechanical enhancement of the phase change homopolymer and their synergistic effects.

In order to study the effects of stress change and adaptability of the overrun hydraulic stent under impact load, the rigid–flexible coupling numerical model of the stent is established using multi-body dynamics simulation software ADAMS. In the model, the stent is flexibilized using the HyperMesh module, and the column and jack are equivalently replaced with a spring damping system. By applying impact loads to different positions above the front roof beam of the stent, the dynamic response characteristics of the column and the articulation point are obtained at different positions with different strengths. The results show that when the impact load is applied to different positions of the front roof beam, the steady-state response force of the column shows an overall “M" distribution, and along the length direction of the roof beam, the steady-state response force of the column shows an upward trend, and the maximum steady-state response force of the column is 547 kN at point (1, 6); when the impact load is applied to both sides of the front roof beam, the response at the articulation point is greater, resulting in a higher maximum simple harmonic response at that articulation point. When the impact load acts on both sides of the front roof beam, the response of the articulation point is greater, with a maximum simple harmonic response coefficient of 0.75 and a maximum excitation response coefficient of 0.28; when the impact loads of different strengths act on the whole front roof beam, the force acting on the column and pin shaft at the articulation point will produce a large impact, reducing its adaptability. To address this, we can consider changing the top plate stress conditions using methods like high-pressure injection of water and control the gradual and slow release of the top plate stresses. The results of the study provide a reference for the structural strength design and reliability analysis of the hydraulic support, which is of practical significance and value for improving the safe mining of the coal mining face.

Purpose – This study aims to evaluate the characteristics of climate change in Yunnan minority areas and identify an effective path to promote sustainable livelihoods based on climate change. Design/methodology/approach – Taking Yunnan Province as an example, based on the expansion of the traditional sustainable livelihood framework, the authors constructed a system dynamics (SD) model of sustainable livelihood from the six subsystems of natural, physical, financial, social, human and cultural and tested the accuracy and effectiveness of the model with data from Cangyuan County. By adjusting these parameters, five development paths are designed to simulate the future situation of the livelihood system and determine the optimal path. Findings – Climate change has exacerbated the vulnerability of people’s livelihoods. In future, each of the five development paths will be advantageous for promoting sustainable livelihoods. However, compared with Path I (maintaining the status quo), Path III (path of giving priority to culture) and Path IV (path of giving priority to economic development) have more obvious advantages. Path II (path of giving priority to people’s lives) gradually increases the development rate by promoting people’s endogenous motivation, and Path V (path of coordinated development) is better than the other paths because of its more balanced consideration. Originality/value – The analytical framework of sustainable livelihoods based on the characteristics of minority areas is broadened. By constructing a SD model of the livelihood system, the limitations of traditional static analysis have been overcome and a development path for promoting sustainable livelihoods through simulation is proposed. This study offers a theoretical framework and reference method for livelihood research against the backdrop of climate change and a decision-making basis for enhancing climate adaptability and realizing sustainable livelihoods.

The gravity wave produced by typhoons has been an essential subject of study that concerns numerous researchers. The damage to human beings and infrastructure in coastal regions caused by typhoon disasters annually is very severe, and analyzing gravity wave variation is a reliable approach to research typhoons. High-frequency surface wave radar (HFSWR) as an over-the-horizon radar can achieve real-time monitoring of an extensive sea area and space. This paper derived the gravity wave perturbation spectrum by handling high-frequency surface wave radar data during typhoons. The gravity wave spectrum data were examined by applying the chaos examination approaches of the Lyapunov exponent and phase-space reconstruction to the gravity wave spectrum data after processing and extraction. The reconstructed phase space had a specific shape in a certain direction, with the maximum Lyapunov exponent greater than zero. The gravity wave spectrum data are suggested to have chaotic properties through two chaos examination approaches. This paper demonstrated that the gravity waves observed by a radar have chaotic properties through the measurement data of HFSWR. While the chaotic properties suggest that observed gravity wave data are predictable in the short term, they are unpredictable in the long term. Predicting gravity wave data is important for understanding the chaotic properties of the atmosphere and for future gravity wave prediction.

Tire appearance defect detection based on machine vision is an effective technology to improve the tire production quality. The detection process can be completed by the way of non-destructive testing. Therefore, more and more researchers are paying attention to this technology. However, tires are characterized by single block colors and various defects. It is a great challenge to accurately detect tire appearance defects. To complete the task of detecting tire defects, this paper presents a novel tire appearance defect detection method via combining histogram of oriented gradients (HOG) and local binary pattern (LBP) features. First, we construct a tire image dataset to provide defective and normal tire images. Then, histogram of oriented gradients and local binary pattern features of tire images are, respectively, extracted and used to train the support vector machine (SVM) classifier. Finally, the support vector machine classifier calculates the prediction scores of the test images via combining the histogram of oriented gradients and local binary pattern features. These scores can be utilized to determine whether the test image is a defective or a normal tire image, and the goal of tire appearance defect detection is achieved. Conducted on the tire image dataset, our method has verified the effectiveness of detecting tire detects, and the mean accuracy is improved more than 1.6% than the algorithm that only uses the histogram of oriented gradients or local binary pattern feature. The experimental results demonstrate that the combination of HOG and LBP features can increase tire appearance defect detection accuracy.

Lamb wave is widely concerned in damage detection of composite structures due to its long propagation distance and strong sensitivity to damage. In order to solve the problem of damage information extraction, high-precision imaging positioning of damage is realized. A damage location imaging method based on lamb signal spectrum is proposed. The damage location imaging of composite materials is realized by simulation and experiment respectively. Firstly, the feasibility of the algorithm is verified by simulation. The circular sensor array is arranged in the structure. Each sensor acts as an actuator and rotates clockwise to generate Lamb waves, while other sensors collect signals. The frequency spectrum of the signal is extracted to calculate the damage factor, and the probability imaging algorithm is used to realize the single damage and multiple damage location imaging. Then, the damage imaging localization is realized through experiments. Finally, the resistant noise characteristic of the proposed algorithm is analyzed. The results show that both single damage and multiple damage can be located in strong noise environment. It shows that this method can realize damage imaging directly without preprocessing the original signal. It has great potential in damage location imaging under strong noise environment.

Concrete is used in the construction of high-rise buildings, large bridges, viaducts and other structures for a wide range of applications, and damage to the internal structure of concrete may to lead to catastrophic accidents. In this paper, electrical resistance tomography is applied to concrete structural damage detection. The electrical resistance tomography imaging reconstruction algorithm is studied. The advantages and disadvantages of five image reconstruction algorithms are investigated through simulation experiments as well as experiments, and the improved normalized image reconstruction algorithm is selected. The feasibility of the used electrical resistance tomography system is explored by conducting imaging experiments with water bodies, and the results show that the built system is feasible. Finally, using the resistive chromatography imaging system, a current excitation is applied to the concrete, and the data acquisition system collects the boundary voltage values carrying the internal conductivity distribution of the concrete, and images its internal structure through the image reconstruction algorithm. It is achieved to detect damage inside the concrete and to visualize the imaging when there are pores in the concrete structure and when water penetrates in the concrete structure.

As an essential regional planning policy, poverty alleviation relocation has a significant impact on the regional economy, environment, and social well-being and is critical for sustainable development. Based on the development of minority areas in Yunnan, this study improves the traditional sustainable livelihood analysis framework and constructed a livelihood capital evaluation system including natural, physical, financial, social, human, and cultural capital. Furthermore, the measurement standard of sustainable livelihoods is proposed, which requires not only the enhancement of livelihood capital but also the coupling and coordinated development of all capital components. Based on the data of Menglai township from 2015 to 2021, this study estimates that farmers’ livelihood capital has increased after relocation, and the level of coupling and coordination has improved. Still, it has yet to reach extreme coordination. Hereafter, the theoretical framework of internal and external factors affecting livelihood capital is constructed, and the influencing factors of livelihood capital are obtained through regression analysis. This study provides a new tool for evaluating livelihood capital in minority areas, obtains new findings on the sustainable development of farmers’ livelihood capital after poverty alleviation relocation, and expands a new perspective for studying the influencing factors of livelihood capital.

ObjectiveGlobally, depression has become a major health issue among older adults, who experience poor physical health and high medical expenditures. In Asian countries, older adults are greatly dependent on their children. This study assessed the impact of different types of intergenerational support and medical expenditures on depression among older adults in rural China.MethodA three-phase balanced panel was constructed based on data from 1,838 rural older adults with comparable scores on the Center for Epidemiologic Studies Depression Scale (CES-D) from the China Family Panel Studies in 2012, 2016, and 2018. A fixed-effects model was used to analyze the impact of intergenerational support and medical expenditures on CES-D score and of intergenerational support on medical expenditures. The propensity score-matching model was used to test the regression results' robustness.ResultsThe findings were as follows. First, different types of intergenerational support had a heterogeneous impact on depression among rural older adults. Emotional support had a significantly negative impact on CES-D score, although too much care-based support had a positive impact on CES-D score. Low-level economic support had no significant effect on CES-D score. Second, medical expenditures impacted depression; among these, non-inpatient medical expenditure had a significant and positive impact on CES-D score. Third, CES-D scores among rural older adults were associated with chronic diseases and per capita family income. Fourth, care-based support was associated with reduced non-inpatient medical expenditures, and the sub-sample regression results indicated that the impact was significant for older adults with no chronic diseases and those younger than 75 years.ConclusionIntergenerational emotional support and non-inpatient medical expenditures directly affected rural older adults' CES-D scores. The mediating role of medical expenditures between intergenerational support and CES-D score was not significant. Measures should be taken to encourage intergenerational emotional support and reduce the pressure on children's economic and care-based support. Further, the medical insurance reimbursement policy, as formal support, should be improved to alleviate depression among rural older adults when children's support is limited.

Woven fabric composite structures are applied in a wide range of industrial applications. Composite structures are vulnerable to damage from working in complex conditions and environments, which threatens the safety of the in-service structure. Damage detection based on Lamb waves is one of the most promising structural health monitoring (SHM) techniques for composite materials. In this paper, based on guided Lamb waves, a lightweight deep-learning approach is proposed for identifying damaged regions in woven fabric composite structures. The designed deep neural networks are built using group convolution and depthwise separated convolution, which can reduce the parameters considerably. The input of this model is a multi-channel matrix transformed by a one-dimensional guided wave signal. In addition, channel shuffling is introduced to increase the interaction between features, and a multi-head self-attention module is designed to increase the model’s global modeling capabilities. The relevant experimental results show that the proposed SHM approach can achieve a recognition accuracy of 100% after only eight epochs of training, and the proposed LCANet has only 4.10% of the parameters of contrastive SHM methods, which further validates the effectiveness and reliability of the proposed method.

Mycoviruses widely exist in filamentous fungi and sometimes cause phenotypic changes in hosts. Trichoderma harzianum hypovirus 1 (ThHV1) and its defective RNA ThHV1-S were found in T. harzianum and exhibited high transmissibility. In our previous study, ThHV1 and ThHV1-S were transferred to an excellent biological control agent T. koningiopsis T-51 to form a derivative strain 51-13. In this study, we assessed the metabolic changes in strain 51-13 and antifungal activity of its culture filtrate (CF) and volatile organic compounds (VOCs). The antifungal activity of CF and VOCs of T-51 and 51-13 was different. Compared with the CF of T-51, that of 51-13 exhibited high inhibitory activity against B. cinerea, Sclerotinia sclerotiorum, and Stagonosporopsis cucurbitacearum but low inhibitory activity against Leptosphaeria biglobosa and Villosiclava virens. The VOCs of 51-13 exhibited high inhibitory activity against F. oxysporum but low inhibitory activity against B. cinerea. The transcriptomes of T-51 and 51-13 were compared; 5531 differentially expressed genes (DEGs) were identified in 51-13 with 2904 up- and 2627 downregulated genes. In KEGG enrichment analysis, 1127 DEGs related to metabolic pathways (57.53%) and 396 DEGs related to biosynthesis of secondary metabolites (20.21%) were clearly enriched. From the CF of T-51 and 51-13, 134 differential secondary metabolites (DSMs) were detected between T-51 and 51-13 with 39 up- and 95 downregulated metabolites. From these, 13 upregulated metabolites were selected to test their antifungal activity against B. cinerea. Among them, indole-3-lactic acid and p-coumaric acid methyl ester (MeCA) exhibited strong antifungal activity. The IC50 of MeCA was 657.35 μM and four genes possibly related to the synthesis of MeCA exhibited higher expression in 51-13 than in T-51. This study revealed the mechanism underlying the increase in antifungal activity of T-51 because of the mycovirus and provided novel insights in fungal engineering to obtain bioactive metabolites via mycoviruses.

The viscoelastic materials exhibit different tribological responses when compared to the stiff materials, due to the intermediate mechanical properties between viscous liquid and elastic solid. In this work, the effect of damping materials viscoelasticity on sliding friction under dry condition was investigated. However, it was difficult to change its damping properties only while other properties (strength or surface hardness) remain unchanged, since viscoelasticity was one of its intrinsic properties. Therefore, the attention of interactions between the material components was closely paid. To achieve this, the experimental groups of damping materials with various viscoelasticity were established by adding various fillers and adjusting their surface properties. Additionally, a viscoelastic property determined friction coefficient model was obtained and validated by the molecular dynamic method. The results show that the test model is in good agreement with the experimental results. Meanwhile, tribo-pairs with higher proportion of viscous character had greater oscillations in friction. They also exhibited higher friction coefficient due to the increased contribution of viscoelastic hysteresis losses to friction.

Abstract In the radar array signal processing direction of arrival (DOA), the estimation of weak non-stationary signal is an important and difficult problem when both strong and weak signals are coexisting particularly because the weak non-stationary signals are often submerged in noise. In this paper, we proposed a novelty method to estimate the direction of arrival (DOA) of weak non-stationary signal in scenario for strong non-stationary interference signals and Gaussian white noise. The method utilizes spatial time-frequency distribution (STFD) of cross terms rather than suppressing cross terms in time-frequency analysis. The STFD of cross terms are introduced as an alternative matrix, which is similar to data covariance matrix in multiple signal classification (MUSIC), for the DOA estimation of a weak non-stationary signal. The cross-term amplitude of the strong and weak signals is usually above the noise and is easier to use than the auto-term of the weak signal. In the cross term, the information of the weak signal is included, and the auto-term of these weak signals is difficult to extract directly. The ability to incorporate the STFD of cross terms empowers information about a weak non-stationary signal for DOA estimation, leading to improved signal estimates for direction finding. The method based on the STFD of cross terms for DOA estimation of the weak non-stationary signal is revealed to outperform the time-frequency MUSIC and traditional MUSIC algorithm by simulation, respectively. This method has the advantages of the time-frequency direction finding method and also deals with the situation of weak signals. When the strong and weak signals exist at the same time and the two angles are similar, the cross-terms can be used to perform DOA estimation on the weak signal.

Abstract Network coding (NC) can greatly improve a system’s performance on throughput and channel utilization via corresponding signal processing on the relay side. Implementation of NC in relay-assisted device-to-device (RA-D2D) communications is a promising way to further explore the advantages of RA-D2D communications in cellular systems. This paper proposes a signal processing scheme for RA-D2D which jointly takes into account NC and optimal relay selection. First, the optimal relay user equipment (UE) is selected by jointly considering the end-to-end data rate, end-to-end transmission delay, and relay survival time. Then, in the procedure of signal processing, the transmitted useful signal is combined with interference signal for NC operation, and finally, the original useful signal is recovered at the destination node. Simulation results show that the proposed scheme is able to not only eliminate the interference effectively but also has a superior performance on end-to-end transmission delay, reachability, and amount of transmitted information than that without NC. In particular, signal processing via NC is equivalent to encrypting the signal, which further enhances the information security in D2D communications.

In this study, the changes in quality parameters and sensory-influencing parameters from the peel, red flesh, and white flesh of ‘Yonglian No.1’ peach fruits were analyzed during cold storage. The results indicated that the contents of total soluble solids (TSS), soluble sugar, organic acid, vitamin C, total anthocyanin, phenol, and flavonoids, as well as the good fruit rate varied depending on the storage stages and storage treatments. The peach fruits in MAP stored for 50 days had favorable exterior qualities, a good fruit rate of 100%, and a higher content of total soluble solids (TSS) at 12.6%. MAP was significantly effective at maintaining fruit firmness, the content of TSS, soluble sugar, organic acid, vitamin C, total anthocyanin, phenol, and flavonoids. Among the derivatives of anthocyanin, both cyanidin and pelargonidin were found in the peel, with a content of 33.45 mg/kg FW and 1.82 mg/kg FW, respectively. However, cyanidin was detected in the flesh with a content of 40.42 mg/kg FW. In the present work, the differences regarding phytochemical profiles and physical properties were mainly correlated with the storage stages and storage treatments of peach fruit. ‘Yonglian No.1’ had higher levels of health-promoting compounds during storage and maintained favorable quality.

In this paper, a multiuser multi-antenna relay system with wireless power transfer is investigated, where the relay node harvests energy from the radio frequency signal sent from the source node and utilizes the harvested energy to forward the information signal to users. Under the transmit power constraints at all nodes, the optimization problem is formulated which maximizes the achievable sum rate of the relay system by optimizing the time switching (TS) factor and the source and the relay precoding matrixes. We divide the complex non-convex objective problem into several subproblems which are solved by the proposed alternating optimization (AO) scheme. We also propose a novel power allocation scheme across subchannels to maximize the sum rate. Since the objective function to optimize the relay power allocation is not convex, difference of convex programming is adopted to transform the original non-convex problems into convex optimization problems. Simulation results are provided to verify the analysis and demonstrate the efficiency of the proposed AO scheme.

For the direction-of-arrival (DOA) estimators based on sparse signal representation, the feasibility and precision are greatly restricted by the inherent limitation of the predefined spatial discrete grids. In this paper, based on the high aggregation characteristic of wideband linear frequency modulation signals, we derive the modified fractional domain sparse model (MFDSM) in DOA estimation and propose a novel off-grid DOA estimation method via alternating descent iteration (OGDEADI). The simulation results show that our proposed MFDSM-OGDEADI method has enhanced estimation accuracy and better angular resolution in terms of signal-to-noise ratio, angle difference, grid size, and angle bias, and it also has the advantage of being less sensitive to the grid size.

Trichoderma spp. are widely used in plant disease control and growth promotion due to their high efficacy and multiple biocontrol mechanisms. Trichoderma koningiopsis T-51 is an effective biocontrol agent against gray mold disease by direct contact. However, the indirect physical contact biocontrol potential of Trichoderma spp. is not clear. In this study, the volatile organic compounds (VOCs) produced by T-51 showed high inhibitory activity against plant pathogenic fungi Botrytis cinerea and Fusarium oxysporum. The percentage of B. cinerea and F. oxysporum mycelial growth inhibition by T-51 VOCs was 73.78% and 43.68%, respectively. In both B. cinerea and F. oxysporum, conidial germination was delayed, and germ tube elongation was suppressed when exposed to T-51 VOCs, and the final conidial germination rate of B. cinerea decreased significantly after T-51 treatment. The VOCs from T-51 reduced the Botrytis fruit rot of tomato compared with that noted when using the control. Moreover, the T-51 VOCs significantly increased the size and weight of Arabidopsis thaliana seedlings. Twenty-four possible compounds, which were identified as alkenes, alkanes, and esters, were detected in VOCs of T-51. These results indicate that T. koningiopsis T-51 can exert biological control by integrating actions to suppress plant disease and promote plant growth.

As an emerging technology, shoot encapsulation has been employed in germplasm conservation, distribution, and micropropagation of elite plant species. However, the production of synthetic seeds of sweet potato via non-zygotic embryogenesis requires a large number of embryos per cultured callus suspension and is labour-intensive. Here, we reported a simple method of encapsulating in vitro derived vegetable sweet potato nodal segments with sodium alginate, calcium chloride (CaCl2), and Murashige and Skoog (MS) salts. The nodes encapsulated with 4% sodium alginate (w/v) and 100 mM CaCl2 were the most suitable for propagation. They had uniform spherical beads and took the least number of days to shoot and root emergence. These plantlets produced more leaves, roots, and long shoots. Further evaluation of the MS salts concentration revealed that the plantlets encapsulated and grown with ½ MS salts had the least days to shoot and root emergence. They also had a longer shoot, the highest conversion rate (99%), and the least leaf abscission (17%). Thus, the sweet potato nodal segments encapsulated with 4% sodium alginate, 100 mM CaCl2, and ½ MS salts could be used as excellent material for micropropagation, germplasm conservation, and exchange of sweet potato planting materials.

A promising way to improve the performance and guarantee the quality of service (QoS) of cognitive wireless cooperative relay networks is to jointly employ physical-layer network coding (PNC) and multi-antenna space-time block coding. This paper proposes a new multi-user transmission coding scheme, cooperative quadrature PNC (CQPNC), for cognitive wireless networks. In CQPNC scheme, two source nodes (users) first use quadrature carriers to transmit signals simultaneously, which are received and processed by a cooperative relay node using the PNC method. The processed signal is then transmitted to the destination node, which makes a combination of the signals from the direct path and relay path to obtain the information transmitted by the source node. Simulation results in difference cases of cognitive wireless networks show that the CQPNC scheme outperforms the traditional cooperation and cooperative network coding transmission schemes on the performance of anti-noise and throughput.

Abstract Underwater acoustic channel (UAC) is one of the most challenging communication channels in the world, owing to its complex multi-path and absorption as well as variable ambient noise. Although adaptive equalization could effectively eliminate the inter-symbol interference (ISI) with the help of training sequences, the convergence rate of equalization in sparse UAC decreased remarkably. Besides, channel estimation algorithms could roughly figure out channel impulse response and other channel parameters through several specific mathematical criterions. In this paper, a typical channel estimation method, least square (LS) algorithm, is applied in adaptive equalization to obtain the initial tap weights of least mean square (LMS) algorithm. Simulation results show that the proposed method significantly enhances the convergence rate of the LMS algorithm.

A simple, high-sensitivity, and low-cost optical sensor for the measurement of temperature and salinity in seawater is demonstrated based on a microfiber directional coupler. The shifts of sensing dips are highly sensitive to the change of salinity and temperature in seawater with highest sensitivities at 930 pm/% and -160 pm/°C for coupler assembled by 3.79and 2.20-μm-diameter fibers. The temperature sensitivity can be further improved to -1130 pm/°C for smaller fibers with diameters of 3.50 and 1.35 μm. To keep the stable structure in liquid, a methodology of coating using ethyl cellulose ethoce film is proposed. By ethyl cellulose ethoce solvent coating on the coupling area, the coupler can be operated stably in seawater. The sensor demonstrated here is easy to construct, is low cost, is high sensitivity, and is compatible with the optical fiber system, which may find applications in developing miniature and multifunction optical sensors used in seawater and other liquid surroundings.

The microfiber knot-type ring resonator is widely used in sensing, and the resonant mode is an essential concern. In this paper, resonant mode characteristics of microfiber knot-type ring resonator are studied theoretically. Results show that resonant mode split occurs when the deviation angle is large enough under the condition that the input is linearly or elliptically polarized light. Moreover, in the case that the input is partially polarized light, the resonant peak positions of split modes are identical with those in the case of inputting linearly or elliptically polarized light under the same deviation angle. The split mode characteristic is further studied by salinity sensing simulation and experiment. The split modes have the same free spectral range, and their resonant peak shifts have the same response to salinity changing. The experimental split mode characteristic is in good agreement with theoretical simulating, which demonstrates the resonant mode split theory of the microfiber knot-type ring resonator. The analysis on resonant mode presented here may offer useful references for sensing applications.

Ocean internal-wave phenomena occur with the variation in seawater vertical temperature, and most internal-wave detections are dependent on the measurement of seawater vertical temperature. A seawater temperature sensor based on a microfiber knot resonator (MKR) is designed theoretically and demonstrated experimentally in this paper. Especially, the dependences of sensing sensitivity on fiber diameter and probing wavelength are studied. Calculated results show that sensing sensitivity increases with the increasing microfiber diameter with the range of 2.30–3.91 μm and increases with the increasing probing wavelength, which reach good agreement with results obtained by experiments. By choosing the appropriate parameters, the maximum sensitivity measured can reach to be 22.81 pm/°C. The seawater temperature sensor demonstrated here shows advantages of small size, high sensitivity, easy fabrication, and easy integration with fiber systems, which may offer a new optical method to detect temperature of seawater or ocean internal-wave phenomenon and offer valuable reference for assembling micro sensors used for other parameters related to seawater, such as salinity, refractive index, concentration of NO3− and so on.