Search

Ca and Mg are key constituents in surface water that are essential nutrients and vital indicators of water hardness. Rapid on-site measurement of Ca and Mg concentrations in surface water is important. However, traditional laboratory detection methods are complex and time-consuming, and on-site detection is difficult. In this study, a portable surface water detection method was developed using laser-induced breakdown spectroscopy with a miniaturized spectrometer LIBS and a liquid jet device for sample introduction. The device enables the rapid online in situ measurement of elemental concentrations in the water. The limits of detection for the rapid on-site detection of Ca and Mg in surface water were 11.58 and 2.57 mg/L, respectively. We applied this method to assess the concentrations of Ca and Mg in authentic water samples collected from rivers and ponds. The recovery rates for Ca and Mg were 90.83–101.74% and 93.43–108.74%, respectively. This method is suitable for rapid, on-site, and highly sensitive monitoring of Ca and Mg concentrations in the environment.

Abstract Domesticated safflower (Carthamus tinctorius L.) is a widely cultivated edible oil crop. However, despite its economic importance, the genetic basis underlying key traits such as oil content, resistance to biotic and abiotic stresses, and flowering time remains poorly understood. Here, we present the genome assembly for C. tinctorius variety Jihong01, which was obtained by integrating Oxford Nanopore Technologies (ONT) and BGI-SEQ500 sequencing results. The assembled genome was 1,061.1 Mb, and consisted of 32,379 protein-coding genes, 97.71% of which were functionally annotated. Safflower had a recent whole genome duplication (WGD) event in evolution history and diverged from sunflower approximately 37.3 million years ago. Through comparative genomic analysis at five seed development stages, we unveiled the pivotal roles of fatty acid desaturase 2 (FAD2) and fatty acid desaturase 6 (FAD6) in linoleic acid (LA) biosynthesis. Similarly, the differential gene expression analysis further reinforced the significance of these genes in regulating LA accumulation. Moreover, our investigation of seed fatty acid composition at different seed developmental stages unveiled the crucial roles of FAD2 and FAD6 in LA biosynthesis. These findings offer important insights into enhancing breeding programs for the improvement of quality traits and provide reference resource for further research on the natural properties of safflower.

Abstract This study aimed to investigate the effects of exercise on excessive mitochondrial fission, insulin resistance, and inflammation in the muscles of diabetic rats. The role of the irisin/AMPK pathway in regulating exercise effects was also determined. Thirty-two 8-week-old male Wistar rats were randomly divided into four groups (n = 8 per group): one control group (Con) and three experimental groups. Type 2 diabetes mellitus (T2DM) was induced in the experimental groups via a high-fat diet followed by a single intraperitoneal injection of streptozotocin (STZ) at a dosage of 30 mg/kg body weight. After T2DM induction, groups were assigned as sedentary (DM), subjected to 8 weeks of treadmill exercise training (Ex), or exercise training combined with 8-week cycloRGDyk treatment (ExRg). Upon completion of the last training session, all rats were euthanized and samples of fasting blood and soleus muscle were collected for analysis using ELISA, immunofluorescence, RT-qPCR, and Western blotting. Statistical differences between groups were analyzed using one-way ANOVA, and differences between two groups were assessed using t-tests. Our findings demonstrate that exercise training markedly ameliorated hyperglycaemia, hyperlipidaemia, and insulin resistance in diabetic rats (p

Neuroinflammation is a major feature of type 2 diabetic mellitus (T2DM), adversely affecting hippocampal neurogenesis. However, the precise mechanism is not fully understood, and therapeutic approaches are currently lacking. Therefore, we determined the effects of exercise on neuroinflammation and hippocampal neurogenesis in T2DM mice, with a specific focus on understanding the role of the irisin and related cascade pathways in modulating the beneficial effects of exercise in these processes. Ten-week exercise significantly decreased T2DM-induced inflammation levels and markedly promoted hippocampal neurogenesis and memory function. However, these positive effects were reversed by 10 weeks of treatment with cyclo RGDyk, an inhibitor of irisin receptor signaling. Additionally, exercise helped reduce the M1 phenotype polarization of hippocampal microglia in diabetic mice; this effect could be reversed with cyclo RGDyk treatment. Moreover, exercise markedly increased the levels of fibronectin type III domain-containing protein 5 (FNDC5)/irisin protein while decreasing the expression of Toll-like receptor 4 (TLR4), myeloid differential protein-88 (MyD88), and nuclear factor kappa-B (NF-κB) in the hippocampus of T2DM mice. However, blocking irisin receptor signaling counteracted the down-regulation of TLR4/MyD88/NF-κB in diabetic mice undergoing exercise intervention. Conclusively, exercise appears to be effective in reducing neuroinflammation and enhancing hippocampal neurogenesis and memory in diabetes mice. The positive effects are involved in the participation of the irisin/TLR4/MyD88/NF-κB signaling pathway, highlighting the potential of exercise in the management of diabetic-induced cognitive decline.

Background: Sedentary behaviour has been associated with an increased risk of falls among older adults. Although gait initiation (GI) is a promising tool used to assess fall risk, it has yet to be quantitatively evaluated for dynamic stability in sedentary populations. Tai Chi exercise is believed to be effective in preventing falls in older adults, but its effect on GI stability has not been quantified. This study aims to compare the stability of GI in sedentary older individuals versus those who are long-term Tai Chi exercisers by using a quantitative approach.Methods: This study included 17 sedentary older women without exercise habits (age: 65.59 ± 3.66 years, average daily sitting time: 8.735 ± 1.847 h/day) and 19 older women who regularly engage in Tai Chi exercise (age: 65.58 ± 3.63 years, years of exercise: 9.84 ± 3.48 years). Every participant underwent five trials of self-paced GI walking tests. Eight cameras and four force plates were used to obtain kinematic and kinetic parameters. The trajectory of the centre of mass (CoM) and the position of the foot placement were recorded. The anterior–posterior (A-P) and medio–lateral (M-L) dynamic stability at the onset and end moments of the single-legged support was calculated using CoM and gait spatiotemporal parameters. The stepping dynamic stability and foot placement positions of both groups were compared.Results: The Tai Chi group had greater stability in the M-L directions at the swing leg’s toe-off moment and in the M-L and A-P directions at the heel-strike moment, as well as significantly larger step length, step width and step speed during locomotion than sedentary older women. However, the stability in the A-P directions at the swing leg’s toe-off moment and the foot inclination angle was not statistically different between the two groups.Conclusion: Long-term regular Tai Chi exercise can enhance the dynamic stability of GI in older women, and effectively improve their foot placement strategy during GI. The findings further confirm the negative effect of sedentary on the stability control of older women and the positive role of Tai Chi in enhancing their gait stability and reducing the risk of falls.

BackgroundChanges in cognitive control are considered potential factors affecting voluntary motor movements during gait initiation (GI). Simulating environments with higher cognitive resource demands have an effect on the stability of GI task performance, which is of significant importance for assessing fall risk in the older adults and devising fall risk management measures in multiple environments. This study aims to reveal the influence of complex cognitive competitive environment with increased cognitive demands on the dynamic stability during GI in the older women.MethodsTwenty-three older females and twenty-three younger females performed walking tests under three conditions: voluntary initiation (SI), visual light reaction time task (LRT), and cognitive interference + visual light reaction time task (C + LRT). Eight cameras (Qualisys, Sweden, model: Oqus 600) and three force plates (Kistler, Switzerland, model: 9287C) are used to obtain kinematic and kinetic data. To recorde the trajectory of center of pressure (CoP) and the position of the foot placement, and compute the anterior–posterior (A-P) and medio-lateral (M-L) dynamic stability at the onset and end moments of the single-leg support by means of center of mass (CoM) and gait spatiotemporal parameters.ResultsOlder women responded to the effect of complex environments involving cognitive competition on body stability by prolonging the lateral displacement time of the CoP during the anticipatory postural adjustments (APAs) phase, reducing step length and velocity, and increasing step width and foot inclination angle.ConclusionComplex initiation environments lead to competition for cognitive resources in the brain, resulting in decreased stability of GI motor control in older adults. The higher the complexity of the cognitive resource demands environment, the lower the stability of GI in older adults, and the greater the effect on their M-L stability at the onset of stepping.

The BeiDou-3 system (BDS-3) broadcasts PPP-B2b signals to provide real-time PPP service. Compared with the traditional PPP technique, the PPP-B2b service broadcasts corrections through satellite links, covers a wide area, and is independent of the internet. With the PPP-B2b service, users can obtain high-precision positioning information through the real-time PPP. Many studies have been conducted to evaluate the positioning performance of PPP-B2b. In theory, high-precision timing information could also be obtained through PPP-B2b. With the development of science and technology, the need for highly accurate time measurement, even at the sub-nanosecond level, is experiencing significant growth. However, the GNSS standard timing service can hardly meet these requirements. This contribution analyzes the timing performance of the PPP-B2b service and proposes a sub-nanosecond precise timing method of Coordinated Universal Time (UTC) based on the PPP-B2b service. BDS-3 and GPS observations from nine tracking stations and real-time collected PPP-B2b corrections over 516 days were used to analyze the performance of the proposed timing method. The results show that: (1) The difference between the PPP-B2b-restored UTC, which was realized by one-way timing with the UTC offsets in broadcast ephemeris, and UTC (NTSC), fluctuates within a few ns. (2) The timing uncertainty of the zero baseline based on the proposed method is better than 0.2 ns. (3) Compared with the post-processed PPP time transfer, the UTC dissemination uncertainty of the short and long baseline with the proposed method is better than 0.7 ns. The experiment results verified the feasibility of the proposed sub-nanosecond level precise UTC dissemination method based on the PPP-B2b service.

Abnormal electromagnetic radiation associated with seismic activity has been reported across a wide range of frequencies, but its primary energy is concentrated in the super-low-frequency (SLF) and extremely low-frequency (ELF) bands. To estimate the effect of the seismic radiation source, a radiator in a soil foundation was modeled as a horizontal electric dipole (HED), and the propagation characteristics of the electromagnetic fields were studied in the Earth–ionosphere cavity. The expressions of the electromagnetic fields could be obtained according to the reciprocity theorem. Therefore, a new algorithm named the numerical integral algorithm was proposed, which is suitable for both the SLF and ELF bands. The new algorithm was compared with the asymptotic approximation algorithm when the receiving point was not close to the field source and the antipode. The two algorithms were found to be in excellent agreement, confirming the validity of the new algorithm for SLF and ELF bands.

Abstract The mechanisms driving therapeutic resistance and poor outcomes of mantle cell lymphoma (MCL) are incompletely understood. We characterize the cellular and molecular heterogeneity within and across patients and delineate the dynamic evolution of tumor and immune cell compartments at single cell resolution in longitudinal specimens from ibrutinib-sensitive patients and non-responders. Temporal activation of multiple cancer hallmark pathways and acquisition of 17q are observed in a refractory MCL. Multi-platform validation is performed at genomic and cellular levels in PDX models and larger patient cohorts. We demonstrate that due to 17q gain, BIRC5/survivin expression is upregulated in resistant MCL tumor cells and targeting BIRC5 results in marked tumor inhibition in preclinical models. In addition, we discover notable differences in the tumor microenvironment including progressive dampening of CD8+ T cells and aberrant cell-to-cell communication networks in refractory MCLs. This study reveals diverse and dynamic tumor and immune programs underlying therapy resistance in MCL.

Air temperature (Ta) is a common meteorological element involved in many fields, such as surface energy exchange and water circulation. Consequently, accurate Ta estimation is essential for the establishment of hydrological, climate, and environmental models. Unlike most studies concerned with the estimation of daily Ta from land surface temperature, this study focused on the estimation of instantaneous Ta from Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric profile products aboard the Terra and Aqua satellites. The applicability of various estimation methods was examined in two regions with different geomorphological and climate conditions, North and Southwest China. Specifically, the spatiotemporal trend of Ta under clear sky conditions can be reflected by the atmospheric profile extrapolation and average methods. However, the accuracy of Ta estimation was poor, with root mean square error (RMSE) ranging from 3.5 to 5.2 °C for North China and from 4.0 to 7.7 °C for Southwest China. The multiple linear regression model significantly improved the accuracy of Ta estimation by introducing auxiliary data, resulting in RMSE of 1.6 and 1.5 °C in North China and RMSE of 2.2 and 2.3 °C in Southwest China for the Terra and Aqua datasets, respectively. Since atmospheric profile products only provide information under clear sky conditions, a new multiple linear regression model was established to estimate the instantaneous Ta under cloudy sky conditions independently from atmospheric profile products, resulting in RMSE of 1.9 and 1.9 °C in North China and RMSE of 2.5 and 2.8 °C in Southwest China, for the Terra and Aqua datasets, respectively. Finally, instantaneous Ta products with high accuracy were generated for all-weather conditions in the study regions to analyze their Ta spatial patterns. The accuracy of Ta estimation varies depending on MODIS datasets, regions, elevation, and land cover types.

Agasicles hygrophila Selman and Vogt (Coleoptera: Chrysomelidae) is the key natural enemy of Alternanthera philoxeroides (Mart.) Griseb, an invasive weed worldwide. To understand the morphology of A. hygrophila and further explore the specific host localization mechanism, scanning electron microscopy was used to observe and study the morphological characteristics of sensilla on the head appendages, tarsi, and external genital segments of A. hygrophila. Twelve types and forty-six subtypes of sensilla were observed. These contain various types of head appendices, including sensilla chaetica, sensilla trichodea, sensilla basiconca, sensilla coeloconica, sensilla styloconica, Böhm bristles, sensilla campaniform, sensilla terminal, sensilla dome, sensilla digit-like, sensilla aperture, and many subtypes. A new type of sensor was reported for the first time, which may be related to host plant recognition. This sensor was located on the distal segment of the maxillary palps of A. hygrophila and was named as sensilla petal-shaped based on its morphological characteristics. Sensilla chaetica, sensilla trichodea, and sensilla basiconca are also found on the tarsi and external genital segments. In addition, sensilla basiconica 4, sensilla coeloconica 1 and 2, sensilla styloconica 2, Böhm bristles 2, and sensilla campaniform 1 were only found in females. On the contrary, sensilla styloconica 3, sensilla coeloconica 3, and sensilla dome were only found in males. Numbers and sizes of the sensilla were also different between males and females. The potential functions related to structure were discussed in comparison with previous investigations on beetles and other monophagous insects. Our results provide a microscopic morphological basis for further research on the localization and recognition mechanism of A. hygrophila and its obligate host.

Fault diagnosis of industrial equipments is extremely important for the safety requirements of modern production processes. Lately, deep learning (DL) has been the mainstream fault diagnosis tool due to its powerful representational ability in learning and flexibility. However, most of the existing DL-based methods may suffer from two drawbacks: Firstly, only one metric is used to construct networks, thus multiple kinds of potential relationships between nodes are not explored. Secondly, there are few studies on how to obtain better node embedding by aggregating the features of different neighbors. To compensate for these deficiencies, an advantageous intelligent diagnosis scheme termed AE-MSGCN is proposed, which employs graph convolutional networks (GCNs) on multi-layer networks in an innovative manner. In detail, AE is carried out to extract deep representation features in process measurement and then combined with different metrics (i.e., K-nearest neighbors, cosine similarity, path graph) to construct the multi-layer networks for better multiple interaction characterization among nodes. After that, intra-layer convolutional and inter-layer convolutional methods are adopted for aggregating extensive neighbouring information to enrich the representation of nodes and diagnosis performance. Finally, a benchmark platform and a real-world case both verify that the proposed AE-MSGCN is more effective and practical than the existing state-of-the-art methods.

Aiming at the typical faults in the coal mills operation process, the kernel extreme learning machine diagnosis model based on variational model feature extraction and kernel principal component analysis is offered. Firstly, the collected signals of vibration and loading force, corresponding to typical faults of coal mill, are decomposed by variational model decomposition, and the intrinsic model functions at different scales are obtained. Then, the eigenvectors consisting of feature energy and sample entropy in these functions are respectively calculated, and the kernel principal component analysis is used for noise removal and dimensionality reduction. Finally, the kernel extreme learning machine model is trained and tested with the dimension reduced feature vector as input and the corresponding coal mill state as output. The results show that the variational model decomposition extraction can improve the input features of the model compared with the single eigenvector model, and the kernel principal component analysis method can significantly reduce the information redundancy and the correlation of eigenvectors, which can effectively save time and cost, and improve the prediction performance of the model to some extent. The establishment of this model provides a new idea for the study of coal mill fault diagnosis.

Insulin resistance is recognized as one major feature of metabolic syndrome, and frequently emerges as a difficult problem encountered during long-term pharmacological treatment of diabetes. Insulin resistance often causes organs or tissues, such as skeletal muscle, adipose, and liver, to become less responsive or resistant to insulin. Exercise can promote the physiological function of those organs and tissues and benefits insulin action via increasing insulin receptor sensitivity, glucose uptake, and mitochondrial function. This is done by decreasing adipose tissue deposition, inflammatory cytokines, and oxidative stress. However, understanding the mechanism that regulates the interaction between exercise and insulin function becomes a challenging task. As a novel myokine, irisin is activated by exercise, released from the muscle, and affects multi-organ functions. Recent evidence indicates that it can promote glucose uptake, improve mitochondrial function, alleviate obesity, and decrease inflammation, as a result leading to the improvement of insulin action. We here will review the current evidence concerning the signaling pathways by which irisin regulates the effect of exercise on the up-regulation of insulin action in humans and animals.

Variational mode decomposition is an adaptive nonrecursive signal decomposition and time-frequency distribution estimation method. The improper selection of the decomposition number will cause under decomposition or over decomposition, and the improper selection of the penalty factor will affect the bandwidth of modal components, so it is very necessary to look for the optimal parameter combination of the decomposition number and the penalty factor of variational mode decomposition. Hence, differential evolution algorithm is used to look for the optimization combination of the decomposition number and the penalty factor of variational mode decomposition because differential evolution algorithm has a good ability at global searching. The method is called adaptive variational mode decomposition technique with differential evolution algorithm. Application analysis and discussion of the adaptive variational mode decomposition technique with differential evolution algorithm are employed by combining with the experiment. The conclusions of the experiment are that the decomposition performance of the adaptive variational mode decomposition technique with differential evolution algorithm is better than that of variational mode decomposition.

Medicine and food homology (MFH) materials are rich in polysaccharides, proteins, fats, vitamins, and other components. Hence, they have good medical and nutritional values. Polysaccharides are identified as one of the pivotal bioactive constituents of MFH materials. Accumulating evidence has revealed that MFH polysaccharides (MFHPs) have a variety of biological activities, such as antioxidant, immunomodulatory, anti-tumor, hepatoprotective, anti-aging, anti-inflammatory, and radioprotective activities. Consequently, the research progress and future prospects of MFHPs must be systematically reviewed to promote their better understanding. This paper reviewed the extraction and purification methods, structure, biological activities, and potential molecular mechanisms of MFHPs. This review may provide some valuable insights for further research regarding MFHPs.

Cytochrome P450 (CYP) monooxygenases comprise a superfamily of proteins that detoxify xenobiotics and plant secondary metabolites in insects. The CYP6 family is unique to the class Insecta, and its members participate in the metabolism of exogenous substances. In this study, we sequenced and characterized the full-length cDNAs of eight CYP6 family genes from Grapholita molesta (Busck), a global pest of pome fruits. P450 genes with the exception of CYP6AN35, which was most highly expressed in adults, consistently showed high expression in third- or fourth-instar larvae. The analysis of different tissues of adults showed that most of these genes were predominantly expressed in the midgut, Malpighian tubules, and/or fat body. The expression of these eight CYP6 genes was differentially affected by three representative insecticides: malathion (organophosphate), deltamethrin (pyrethroid), and chlorantraniliprole (carbamate). All eight CYP6 genes responded to malathion treatment. Only three CYP6 genes were highly expressed in deltamethrin-treated individuals. Chlorantraniliprole treatment exerted weak effects on gene expression. Interestingly, CYP6AN35 was a highly expression level in the adult head and its expression was induced by all three insecticides. CYP6AN35 may be a key gene in the metabolism of insecticides. This study provides a fundamental understanding of the functions of the CYP6 gene family in insecticide metabolism in G. molesta.

Soft tissue sarcomas (STS) is a set of rare malignant tumor originated from mesoderm. For the prognosis of sarcoma, early diagnosis is important, however, currently no mature and non-invasive method for diagnosis exists. MicroRNAs (miRNAs) are a class of noncoding RNAs and their expression varies greatly, especially during tumor activity. The purpose of this study was to construct a predictive model for the diagnosis of sarcomas based on the relative expression level of miRNA in serum. miRNA array expression data of 677 samples including 402 malignant sarcoma samples and 275 healthy samples was used to construct the prediction model. Based on 6 gene pairs, random generalized linear model (RGLM) was constructed, with an accuracy of 100% in the internal test dataset and of 74.3% in the merged external dataset in prediction whether a serum sample was obtained from a sarcoma patient, with a specificity of 100% in the internal test dataset and 90.5% in the external dataset. In conclusion, our serum miRNA-pair classifier has the potential to be used for the screening of sarcoma with high accuracy and specificity.

In this paper, tracking controller and synchronization controller of the Arneodo chaotic system with uncertain parameters and input saturation are considered. An adaptive tracking control law and an adaptive synchronization control law are proposed based on backstepping and Lyapunov stability theory. The adaptive laws of the unknown parameters are derived by using the Lyapunov stability theory. To handle the effect caused by the input saturation, an auxiliary system is used to compensate the tracking error and synchronization error. The proposed adaptive tracking control and synchronization schemes ensure the effects of tracking and synchronization. Several examples have been detailed to illuminate the design procedure.

Background: Osteosarcoma (OS) is one of the malignant bone tumors occurring in both human and canine, and in both of them, it is characterized by a high rate of metastasis and poor prognosis. Cross-species analysis reveals previously neglected molecular or signaling pathways involved in the progression of diseases, and dogs are genetically comparable to humans and live in similar environments. Therefore, the aim of this study was to find out OS hub genes through a cross-species analysis.Materials and Methods: All the human and canine OS gene expression data obtained by the Affymetrix platform were collected. After quality assessment and normalization, co-expression network was performed using weighted gene co-expression network analysis (WGCNA). Species-specific modules and consensus modules were identified. Protein–protein interaction (PPI) networks analysis was performed based on consensus gene modules. Then, consensus modules were functionally annotated and correlated with clinical traits. Hub nodes were identified by a subnetwork analysis of PPI network and WGCNA module membership. Modules of interest and hub nodes were validated in an external data set.Results: Three modules for the human network, seven modules for the canine network, and four consensus modules were identified. The consensus module 3 (C3) showed a significant correlation with the metastatic status in the training data set and a significant correlation with metastasis-free survival in the external data set. Cluster of differentiation 86 (CD86) was identified as the hub gene of C3, showing a significant correlation with metastasis-free survival.Conclusion: Genes in C3 play an important role in OS metastasis, whereas CD86 might be a potential molecular biomarker for OS metastasis.

China is strongly dependent on railway transportation, but the frost heaving of the subgrade in cold regions has seriously affected the safety and comfort of trains. Moisture content is an essential parameter in the subgrade frost heave. Non-destructive and efficient geophysical methods have great potential in measuring the moisture content of railway subgrade. In this paper, we use the common mid-point (CMP) measurement of ground penetrating radar (GPR) to estimate the propagation velocity of electromagnetic waves in a subgrade application. We establish a synthetic model to simulate the railway subgrade structure. The synthetic CMP gathers acquired from shallow and thin layers are seriously disturbed by multiple waves and refraction waves, which make the routine velocity analysis unable to provide accurate velocities. Through the analysis of numerical simulation results, it is found that the primary reflection waves, multiple waves, and refraction waves are dominant in different offset ranges of CMP gather. Therefore, we propose a solution of the optimal gather at a certain range of offset dominated by the primary reflection wave to calculate the velocity spectrum and extract the accurate velocities for the subgrade model. The relative dielectric constants of the corresponding layers are calculated after the stacking velocities are converted into the interval velocities. Then, the moisture content is obtained by the Topp formula, which expresses the relationship between dielectric constant and moisture content. Finally, we apply the optimal gather scheme and the above interpretation process to the GPR data acquired at the railway site, and we form a long moisture content profile of the railway subgrade. Compared with the polarizability measured by the induced polarization (IP) method, it is found that the regions with high moisture content correspond to polarizability anomalies with different strengths. The comparison shows the reliability of GPR results to some extent.

Global warming has gradually reduced the control efficacy of Agasicles hygrophila against the invasive weed Alternanthera philoxeroides. To better understand the summer collapse of A. hygrophila populations, we cloned the cDNA sequences of the high temperature-sensing TRPA1, Painless, and Pyrexia from A. hygrophila, and analyzed their temporal expressions and the impacts of high temperatures on their expression in eggs, the most vulnerable stage of A. hygrophila to hot temperatures. All the three genes obtained had the signature domains of TRPA channels and were constitutively expressed in eggs, larvae (L1, L2, L3), pupae, and adults, but AhPainless had the highest expression, followed by AhPyrexia, and AhTRPA1. The lowest and highest expression stages were adult and pupae for AhTRPA1, egg and L3 for AhPainless, and pupae/adult and L2 for AhPyrexia. The expressions of AhTRPA1, AhPainless, and AhPyrexia remained low at the preferred temperature range of 25–28 °C, elevated to their peak levels at 37.5, 30, and 30 °C, respectively, then fell to their 25–28 °C levels (AhTRPA1, AhPainless) or a lower level (AhPyrexia) at one or more temperatures >30 or 37.5 °C. These results suggest that their temperature-sensing roles and importance may be different, stage-specific, and their expression may be decoupled from their activation.

A borehole radar investigation was performed at the Sanzuodian reservoir, Chifeng, China to assess possible leakage paths located in the deep dam foundation. The key methodologies used include both single-hole reflection and cross-hole radar tomography, which make a high-resolution identification of the hydraulic connection paths between upstream and downstream sides possible. The leakage paths are characterized by direct wave loss due to high electromagnetic attenuation in the single-hole reflection profile and the nearly horizontal-banded low-velocity zone in the cross-hole velocity tomography due to possible large internal erosion. Meanwhile, some small structures inside the dam, including the core wall thickness changing point, the connecting point between asphalt and concrete walls, and the contacting interface between the dry and the water-saturated formations can be identified from the single-hole reflection profile clearly. Interpreted leakage paths are proven by the water flow measurement. Borehole radar is a useful high-resolution tool, suitable for deep leakage detection and evaluation.

In this study, we considered a single rotational degree-of-freedom experimental system, in addition to a mass-spring-damper-friction biomechanical model of the human arm, and then investigated master-slave and master-semi-master cooperative motions. For the master-slave cooperative motion, we developed a mass-spring-friction biomechanical model for the slave's arm. Within the investigated range, we found the damping factor to be zero, and the stiffness and dynamic friction to be individually constant. We also determined the torque characteristics in the master-slave and master-semi-master cooperative motions. In the master-slave cooperative motion, although the master subject had to overcome the entire impedance resistance of the slave subject's arm, the master found it easier to slow down and stop the motion. In master-semi-master cooperative motion, when the semi-master subject switched from passive arm movement to active arm movement, the stiffness characteristics disappeared and constant torque characteristics were observed. At that moment, the master subject felt it took less effort to perform active arm movement. As a result, we assume that in human-robot cooperative tasks, during accelerating motion, we can apply the characteristics of the semi-master to a robot through torque control, and during deceleration (braking) motion, we can apply the slave characteristics to a robot by means of impedance control.