Feature aggregation and region-aware learning for detection of splicing forgery.

Detection of image splicing forgery become an increasingly difficult task due to the scale variations of the forged areas and the covered traces of manipulation from post-processing techniques. Most existing methods fail to jointly multi-scale local and global information and ignore the correlations between the tampered and real regions in inter-image, which affects the detection performance of multi-scale tampered regions. To tackle these challenges, in this paper, we propose a novel method based on feature aggregation and region-aware learning to detect the manipulated areas with varying scales. In specific, we first integrate multi-level adjacency features using a feature selection mechanism to improve feature representation. Second, a cross-domain correlation aggregation module is devised to perform correlation enhancement of local features from CNN and global representations from Transformer, allowing for a complementary fusion of dual-domain information. Third, a region-aware learning mechanism is designed to improve feature discrimination by comparing the similarities and differences of the features between different regions. Extensive evaluations on benchmark datasets indicate the effectiveness in detecting multi-scale spliced tampered regions

Quantitative Assessment of Blood Pressure Measurement Accuracy and Variability from Visual Auscultation Method by Observers without Receiving Medical Training

This study aimed to quantify blood pressure (BP) measurement accuracy and variability with determinations from visualizing Korotkoff sound waveform. Thirty video clips of BP recordings from the educational training database of the British Hypertension Society were converted to Korotkoff sound waveforms. Ten observers without receiving medical training were asked to determine systolic and diastolic BPs (SBP and DBP) from the randomly arranged video clips and Korotkoff sound waveforms using two measurement methods: a) traditional manual auscultatory method of listening for Korotkoff sounds; and b) visual auscultation method by visualising the Korotkoff sound waveform, which was repeated three times on different days, making a total of 6 BP measurements from each observer on each BP recording. The measurement variability was calculated from the standard deviation of the three repeats, and the measurement error was calculated against the reference answers. Statistical analysis showed that, in comparison with the traditional manual auscultatory method, visual auscultation method significantly reduced overall measurement variability from 2.2 to 1.1 mmHg for SBP and from 1.9 to 0.9 mmHg for DBP (both p<0.001). It also showed that BP measurement errors were significant for both techniques (all p<0.01, except DBP from the traditional method). Although significant, the overall mean measurement errors were small, which were -1.5 and -1.2 mmHg for SBP, and -0.7 and 2.6 mmHg for DBP, respectively from the traditional manual auscultatory and visual auscultation methods. In conclusion, the visual auscultation method had the ability to achieve an acceptable degree of BP measurement accuracy, with smaller measurement variability in comparison with the traditional manual auscultatory method

Significantly Reduced Blood Pressure Measurement Variability for Both Normotensive and Hypertensive Subjects: Effect of Polynomial Curve Fitting of Oscillometric Pulses

This study aimed to compare within-subject blood pressure (BP) variabilities from different measurement techniques. Cuff pressures from three repeated BP measurements were obtained from 30 normotensive and 30 hypertensive subjects. Automatic BPs were determined from the pulses with normalised peak amplitude larger than a threshold (0.5 for SBP, 0.7 for DBP, and 1.0 for MAP). They were also determined from cuff pressures associated with the above thresholds on a fitted curve polynomial curve of the oscillometric pulse peaks. Finally, the standard deviation (SD) of three repeats and its coefficient of variability (CV) were compared between the two automatic techniques. For the normotensive group, polynomial curve fitting significantly reduced SD of repeats from 3.6 to 2.5 mmHg for SBP and from 3.7 to 2.1 mmHg for MAP and reduced CV from 3.0% to 2.2% for SBP and from 4.3% to 2.4% for MAP (all P<0.01). For the hypertensive group, SD of repeats decreased from 6.5 to 5.5 mmHg for SBP and from 6.7 to 4.2 mmHg for MAP, and CV decreased from 4.2% to 3.6% for SBP and from 5.8% to 3.8% for MAP (all P<0.05). In conclusion, polynomial curve fitting of oscillometric pulses had the ability to reduce automatic BP measurement variability

Production status and research advancement on root rot disease of faba bean (Vicia faba L.) in China

China is the largest producer of faba bean with a total harvested area of 8.11×105 ha and a total production of 1.69 ×106 tons (dry beans) in 2020, accounting for 30% of the world production. Faba bean is grown in China for both fresh pods and dry seed. East China cultivates large seed cultivars for food processing and fresh vegetables, while northwestern and southwestern China grow cultivars for dry seeds, with an increased production of fresh green pods. Most of the faba bean is consumed domestically, with limited exports. The absence of unified quality control measures and simple traditional cultivation practices contributes to the lower competitiveness of the faba bean industry in international markets. Recently, new cultivation methods have emerged with improved weed control, as well as better water and drainage management, resulting in higher quality and income for producers. Root rot disease in faba bean is caused by multiple pathogens, including Fusarium spp., Rhizoctonia spp., and Pythium spp. Fusarium spp. is the most prevalent species causing root rot in faba bean crops and is responsible for severe yield loss, with different species causing the disease in different regions in China. The yield loss ranges from 5% to 30%, up to 100% in severely infected fields. The management of faba bean root rot disease in China involves a combination of physical, chemical, and bio-control methods, including intercropping with non-host crops, applying rational nitrogen, and treating seeds with chemical or bio-seed treatments. However, the effectiveness of these methods is limited due to the high cost, the broad host range of the pathogens, and potential negative impacts on the environment and non-targeted soil organisms. Intercropping is the most widely utilized and economically friendly control method to date. This review provides an overview of the current status of faba bean production in China, the challenges faced by the industry due to root rot disease, and the progress in identifying and managing this disease. This information is critical for developing integrated management strategies to effectively control root rot in faba bean cultivation and facilitating the high-quality development of the faba bean industry

Development of a Transcriptional Factor PuuR-Based Putrescine-Specific Biosensor in Corynebacterium glutamicum

Corynebacterium glutamicum is regarded as an industrially important microbial cell factory and is widely used to produce various value-added chemicals. Because of the importance of C. glutamicum applications, current research is increasingly focusing on developing C. glutamicum synthetic biology platforms. Because of its ability to condense with adipic acid to synthesize the industrial plastic nylon-46, putrescine is an important platform compound of industrial interest. Developing a high-throughput putrescine biosensor can aid in accelerating the design&ndash;build&ndash;test cycle of cell factories (production strains) to achieve high putrescine-generating strain production in C. glutamicum. This study developed a putrescine-specific biosensor (pSenPuuR) in C. glutamicum using Escherichia coli-derived transcriptional factor PuuR. The response characteristics of the biosensor to putrescine were further improved by optimizing the genetic components of pSenPuuR, such as the response promoter, reporter protein, and promoter for controlling PuuR expression. According to the findings of the study, pSenPuuR has the potential to be used to assess putrescine production in C. glutamicum and is suitable for high-throughput genetic variant screening

Multicell multiuser massive MIMO channel estimation and MPSK signal block detection applying two-dimensional compressed sensing

Abstract For the uplink multicell massive multiple-input multiple-output (MIMO) block fading systems, a two-dimensional smoothed l 0 channel estimation method (2D-SL0-CE) with the aid of virtual channel representation is firstly exploited in this paper, which can jointly estimate the desired multiuser channels of the target cell and the interference links from neighbor cells without inducing pilot contamination. Then, a 2D-SL0 signal detection method (2D-SL0-SD) with the aid of sparse decomposing and the modified 2D s l 0 recovery algorithm is proposed, which can jointly decode M-ary phase-shift keying (MPSK) signal block for whole desired users. Moreover, an improved 2D-SL0-SD is also proposed to remove multiuser interference of neighbor cells in high SNR scenario. Simulation results show that the 2D-SL0-CE method can remove performance floor induced by pilot contamination and need less pilot overhead than the conventional least square (LS) method. When detecting QPSK signal blocks at 12 dB SNR, the 2D-SL0-SD method with perfect channel state information (CSI) can obtain 10−2 BER. Moreover, in the case of 8PSK signals, the 2D-SL0-SD joining with the 2D-SL0-CE can obtain 10−2 BER at 20 dB SNR

Shrimp Shell Catalyst for Biodiesel Production

A high-performance and environmentally friendly shrimp shell catalyst for biodiesel production was prepared by incomplete carbonization of shrimp shell, loading KF on the resultant, and activation at a desired temperature. The dependence of catalytic activity on preparation conditions such as carbonization temperature, loading amount of KF, and activation temperature was investigated. The shrimp shell catalyst was characterized by the Hammett indicator method, thermogravimetric analysis (TGA) and differential thermal analysis (DTA), scanning electron microscope (SEM), N₂ adsorption−desorption, X-ray diffraction (XRD), energy dispersive spectrometer (EDS), element analyzer, and Fourier transform infrared spectrometer (FT-IR). The catalytic performance was evaluated by the transesterification of rapeseed oil with methanol. The results indicated that the optimum preparation conditions were carbonization at 450 °C, loading KF of 25 wt %, and activation at 250 °C. The conversion reached 89.1% using the shrimp shell catalyst when the reaction was carried out at 65 °C with a catalyst amount 2.5 wt %, a methanol/rapeseed oil molar ratio 9:1, and a reaction time of 3 h. The shrimp shell catalyst possesses a porous framework structure, and its catalytic activity for the transesterification came from the active sites formed by the reaction of incompletely carbonized shrimp shell with KF during the activation process. It was found that the shrimp shell catalyst shows high catalytic activity and ecologically friendly properties, having the potential opportunity to be used in biodiesel production process as heterogeneous base catalyst