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Let RR be a unital associative ring. Our motivation is to prove that left derivations in column finite matrix rings over RR are equal to zero and demonstrate that a left derivation d:T→Td:{\mathcal{T}}\to {\mathcal{T}} in the infinite upper triangular matrix ring T{\mathcal{T}} is determined by left derivations dj{d}_{j} in R(j=1,2,…)R\left(j=1,2,\ldots ) satisfying d((aij))=(bij)d\left(\left({a}_{ij}))=\left({b}_{ij}) for any (aij)∈T\left({a}_{ij})\in {\mathcal{T}}, where bij=dj(a11),i=1,0,i≠1.{b}_{ij}=\left\{\begin{array}{ll}{d}_{j}\left({a}_{11}),& i=1,\\ 0,& i\ne 1.\end{array}\right. The similar results about Jordan left derivations are also obtained when RR is 2-torsion free.

This study aimed to clarify the role of pituitary tumor-transforming gene 1 (PTTG1) in proliferation, migration, invasion, and aerobic glycolysis of pancreatic cancer cells, and evaluate the potential of PTTG1 as a therapeutic target. PTTG1 expression in pancreatic cancers was analyzed using the GEPIA databank. In the Panc1 cell with the PTTG1 knockdown or Mia-PaCa2 cells with PTTG1 overexpression, the cell proliferation was evaluated using cell viability curves and colony formation, and wound heal assay and transwell assay were performed to evaluate the migration and invasion, respectively. Furthermore, a western blot was performed to evaluate the expressions of PTTG1, proliferating cell nuclear antigen, E-cadherin, N-cadherin, and c-myc. Meanwhile, the glucose uptake, extracellular acidification rates (ECAR), and oxygen consumption rates (OCR) were analyzed. Our results showed that PTTG1 expression is upregulated in pancreatic cancer, which promoted cell proliferation. Low PTTG1 contributed to higher disease-free survival and overall survival. In Panc1 cell, PTTG1 knockdown resulted in reduced cell viability and colony formation. The migration and invasion abilities of the cells were also reduced in Panc1 with PTTG1 knockdown. Correspondingly, PTTG1 knockdown decreased c-myc expression, glucose uptake, ECAR, and OCR in Panc1 cells. In Mia-PaCa2 cells, PTTG1 overexpression promoted cell proliferation, aerobic glycolysis, and translocation of β-catenin to the nucleus by regulating c-myc. In conclusion, PTTG1 induces proliferation, migration, and invasion, and promotes aerobic glycolysis in pancreatic cancer cells via regulating c-myc, demonstrating the potential of PTTG1 as a therapeutic target.

ABSTRACT China's socialized service industry of agricultural machinery emerged as the times required, which resolved the institutional contradiction between small farm households and large-scale agriculture. However, as cross-operation harvesters are still monitored based on phone calls, the monitoring efficiency and real-time performance are relatively poor. To improve the dynamic monitoring accuracy of harvester working areas, we proposed a working progress monitoring method based on harvester traveling trajectory and header status identification. The position and gap bridge angle information of harvesters was synchronously acquired in real-time. The height of the header above ground was calculated to determine whether the harvester was harvesting on a valid trajectory. Finally, the valid trajectory of the harvester was selected for area calculation. Field experiments showed that the header heights at the working and non-working tracing points collected by the system were discretely distributed at intervals of [0m, 0.5m] and (0.5m, 2m), respectively. The working progress monitoring algorithm proposed in this paper effectively improved the monitoring accuracy of harvester working areas. The mean error between the working areas calculated with identifying the header status and the actual cultivated land area in the five test plots was 0.09 hm2, with a mean error rate of 3.10%, 8.59% lower than that without identifying the harvester header status.

Rice production is highly seasonal, and the timing for conducting harvest operations has a relatively significant impact on yields, especially the appropriate timing of the harvesting operations. Using scientific methods to monitor the appropriate harvest period can effectively reduce harvesting losses. Most of the existing studies in this field focus on yield changes that occur during the harvest period of rice and also use multispectral remote sensing for inversion of the crop canopy. However, there has been no research on combining the yields and spectral characteristics of the harvest period. In this article, a monitoring method for the appropriate harvest period of rice based on multispectral remote sensing was established. Remote sensing data of the rice canopy were acquired using UAV equipped with multispectral (550 nm, 660 nm, 735 nm, and 790 nm) cameras, and physiological characteristic data of rice moisture content, thousand-grain weight, and tassel ratios were determined simultaneously. Single-band and combined-band spectral reflectance were introduced as model input variables to compare the BP neural network, SVM, and decision tree; a quantitative inversion model of the physiological characteristics of rice was established. The accuracy of the inversion model with different input variables and model methods was evaluated, and the optimal inversion model for rice moisture content and thousand-grain weight was selected, which could be used to determine whether the crop was harvested during the appropriate period. The continuous monitoring of two rice varieties (South Japonica 46 and South Japonica 5055) indicated that the moisture content of South Japonica 46 decreased linearly during the 20-day trial period, while its thousand-grain weight showed a trend of increasing first and then decreasing. The moisture content of South Japonica 5055 showed a fluctuating downward trend, and its thousand-grain weight also showed a trend of increasing first and then decreasing. The spectral reflectance at 735 nm increased gradually, and that of both rice varieties increased from about 35% at the beginning of the trial to about 75% in the later stage. The spectral reflectance at the other three bands did not show significant change with the harvest date. The inverse model of spectral reflectance with rice thousand-grain weight and moisture content was established using the BP neural network, SVM, and decision tree. In single-band inversion models, the regression effect at 735 nm was relatively good in the BP neural network model, with the highest determination coefficients of spectral reflectance and thousand-grain weight of both rich varieties and the smallest RMSE of prediction results. In combined-band inversion models, the regression effects at 550 + 660+735 nm and 660 + 735+790 nm were the best in the SVM and thousand-grain weight inversion models.

In this paper, we propose a new type of tri-input tunneling field-effect transistor (Ti-TFET) that can compactly realize the “Majority-Not” logic function with a single transistor. It features an ingenious T-shaped channel and three independent-biasing gates deposited and patterned on its left, right, and upper sides, which greatly enhance the electrostatic control ability between any two gates of all the three gates on the device channel and thus increase its turn-on current. The total current density and energy band distribution in different biasing conditions are analyzed in detail by TCAD simulations. The turn-on current, leakage current, and ratio of turn-on/off current are optimized by choosing appropriate work function and body thickness. TCAD simulation results verify the expected characteristics of the proposed Ti-TFETs in different working states. Ti-TFETs can flexibly be used to implement a logic circuit with a compact style and thus reduce the number of transistors and stack height of the circuits. It provides a new technique to reduce the chip area and power consumption by saving the number of transistors.

Plant organelles predominantly rely on the actin cytoskeleton and the myosin motors for long-distance trafficking, while using microtubules and the kinesin motors mostly for short-range movement. The distribution and motility of organelles in the plant cell are fundamentally important to robust plant growth and defense. Chloroplasts, mitochondria, and peroxisomes are essential organelles in plants that function independently and coordinately during energy metabolism and other key metabolic processes. In response to developmental and environmental stimuli, these energy organelles modulate their metabolism, morphology, abundance, distribution and motility in the cell to meet the need of the plant. Consistent with their metabolic links in processes like photorespiration and fatty acid mobilization is the frequently observed inter-organellar physical interaction, sometimes through organelle membranous protrusions. The development of various organelle-specific fluorescent protein tags has allowed the simultaneous visualization of organelle movement in living plant cells by confocal microscopy. These energy organelles display an array of morphology and movement patterns and redistribute within the cell in response to changes such as varying light conditions, temperature fluctuations, ROS-inducible treatments, and during pollen tube development and immune response, independently or in association with one another. Although there are more reports on the mechanism of chloroplast movement than that of peroxisomes and mitochondria, our knowledge of how and why these three energy organelles move and distribute in the plant cell is still scarce at the functional and mechanistic level. It is critical to identify factors that control organelle motility coupled with plant growth, development, and stress response.

Author(s): Ning Zhang [1]; Zhenqian Wang [1]; Bo Sun [2]; Long Zhang [1]; Jianping Hu [1]; Xiao Jiang [1]; Xinyun Xu (corresponding author) [3]; Han Chen (corresponding author) [1] Introduction [...], Purpose: The current study aimed to examine risk factors in patients with papillary thyroid microcarcinoma (PTMC) by building a nomogram model to evaluate the probability of central lymph node metastasis (CLNM). Materials and Method: A retrospective study was conducted on 775 patients with PTMC who had thyroid surgery, with a focus on examining the clinical characteristics and sonographic features of these individuals, among which 543 individuals were assigned to the training cohort and 232 individuals to the validation one. Both univariate and multivariate logistic regression analyses were employed to ascertain the risk factors linked to the occurrence of CLNM in individuals with PTMC. Results: Four variables encompassing clinical and ultrasound characteristics were identified to be potential risk factors. These variables include age (OR = 0.814, P = 0.001), gender (OR = 1.974, P = 0.005), tumor size (OR = 3.278, P = 0.001), and microcalcification (OR = 2.542, P = 0.001). All of the aforementioned components were employed to develop a nomogram for the prediction of the occurrence of CLNM in PTMC patients. These findings showed within the range of 0.11 to 0.47, the nomogram demonstrated a consistent ability to accurately forecast the occurrence of CLNM. Conclusions: Risk factors derived from clinical and sonographic features were determined and used to establish a nomogram, and the result demonstrated good performance of the CLNM-predicting nomogram, which may aid doctors in making better clinical decisions regarding the management of PTMC patients. Keywords: Central lymph node metastasis, individualized treatment, nomogram, papillary thyroid microcarcinoma

A doorframe-typed swing seedling pick-up device for automatic field transplanters was developed and evaluated in a laboratory. The device, consisting of a path manipulator and two grippers, can move the pins slowly to extract seedlings from the tray cells and return quickly to the pick-up point for the next extraction. The path manipulator was constructed with the creative design of type-II mechanism combination in series. It consists of an oscillating guide linkage mechanism and a grooved globoidal cam mechanism. The gripper is a pincette-type mechanism using the pick-up pins to penetrate into the root mass for seedling extraction. The dynamic analysis of the designed seedling pick-up device was simulated with ADAMS software. Being the first prototype, various performance tests under local production conditions were conducted to find out the optimal machine operation parameters and transplant production conditions. As the gripper with multiple fine pins was moved by the swing pick-up device, it can effectively complete the transplanting work cycle of extracting, transferring, and discharging a seedling. The laboratory evaluation showed that the pick-up device equipped with two grippers can extract 80 seedlings/min with a 90% success and a 3% failure in discharging seedlings, using 42-day-old tomato plantlets. The quality of extracting seedlings was satisfactory.

Intolerance of uncertainty (IU) has been suggested to be associated with emotional perceptions and evaluations. Several studies have also revealed that IU is related to cognitive preferences, in particular gain-relevant risk preference. Nevertheless, it is still unclear whether both prospective and inhibitory IU, two dimensions of IU, predict gain-related and moreover, loss-relevant risky preference. More importantly, it is unknown whether the associations between IU and risk preference are modulated by biological factors (e.g., genes). Therefore, the current study investigated whether prospective and inhibitory IU were associated with gain-/loss-related risk preference and whether the associations were modulated by an impulsivity control-related gene, tryptophan hydroxylase 1 (TPH1) gene (A779C, rs1799913) through recruiting 222 healthy Chinese participants. Results showed that prospective IU was correlated with gain-relevant risk averse. There was not a significant association between IU and loss-relevant risk preference. Nevertheless, further analysis revealed that the association was modulated by the TPH1 genotype. Prospective and inhibitory IU predicted loss-relevant risk averse specifically for TPH1 AC genotype carriers but not for other genotype carriers (i.e., AA or CC). The findings emphasize the associations between IU and risk preference depending on frame and genetic variance., Author(s): Huiyan Lin [sup.1] [sup.2] , Junkai Yang [sup.1] , Jianping Hu [sup.1] Author Affiliations: (1) https://ror.org/04grzdh47, grid.464294.9, 0000 0004 1805 7312, Laboratory for Behavioral and Regional Finance, Guangdong University [...]

Abstract Background Mortality statistics are key inputs for evidence based health policy at national level. Little is known of the empirical basis for mortality statistics in China, which accounts for roughly one-fifth of the world's population. An adequate description of the evolution of mortality registration in China and its current situation is important to evaluate the usability of the statistics derived from it for international epidemiology and health policy. Current situation The Chinese vital registration system currently covers 41 urban and 85 rural centres, accounting for roughly 8 % of the national population. Quality of registration is better in urban than in rural areas, and eastern than in western regions, resulting in significant biases in the overall statistics. The Ministry of Health introduced the Disease Surveillance Point System in 1980, to generate cause specific mortality statistics from a nationally representative sample of sites. Currently, the sample consists of 145 urban and rural sites, covering populations from 30,000 – 70,000, and a total of about 1 % of the national population. Causes of death are derived through a mix of medical certification and 'verbal autopsy' procedures, applied according to standard guidelines in all sites. Periodic evaluations for completeness of registration are conducted, with subsequent corrections for under reporting of deaths. Conclusion Results from the DSP have been used to inform health policy at national, regional and global levels. There remains a need to critically validate the information on causes of death, and a detailed validation exercise on these aspects is currently underway. In general, such sample based mortality registration systems hold much promise as models for rapidly improving knowledge about levels and causes of mortality in other low-income populations.