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Streptococcus dysgalactiae infection can cause bovine mastitis and lead to huge economic losses for the dairy industry. The abuse of antibiotics has resulted in growing drug resistance of S. dysgalactiae, which causes hard-to-treat infections. Bacteriophage lysin, as a novel antibacterial agent, has great potential for application against drug-resistant gram-positive bacteria. However, few studies have been conducted on the prophage lysin of S. dysgalactiae. In this study, we mined a novel prophage lysin, named Lys1644, from a clinical S. dysgalactiae isolate by genome sequencing and bioinformatic analysis. Lys1644 was expressed and purified, and the lytic activity, antibacterial spectrum, optimal pH and temperature, lytic activity in milk in vitro, and synergistic bacteriostasis with antibiotics were assessed. The Lys1644 prophage lysin showed high bacteriolysis activity specifically on S. dysgalactiae, which resulted in CFU 100-fold reduction in milk. Moreover, Lys1644 maintained high activity over a wide pH range (pH 5–10) and a wide temperature range (4–42 °C). Synergistic bacteriostatic experiments showed that the combination of low-dose Lys1644 (50 μg/mL) with a subinhibitory concentration of aminoglycoside antibiotics (kanamycin or spectinomycin) can completely inhibit bacterial growth, suggesting that the combination of Lys1644 and antibiotics could be an effective therapeutic strategy against S. dysgalactiae infection. [ABSTRACT FROM AUTHOR]

This study aims to investigate the probiotic properties of various isolated strains of Lactiplantibacillus plantarum. Specifically, the focus is on examining the expression of the glutamic acid decarboxylase (GAD) gene and its role in the production of gamma-aminobutyric acid (GABA), a promising postbiotic metabolite. The investigation includes comprehensive analyses of morphology, genetics, resilience against bile, NaCl, and simulated pancreatin juice (SPJ), carbohydrate fermentation patterns, antibacterial activity, susceptibility to antibiotics, and the presence of β-D-galactosidase and GAD enzymes. Six L. plantarum strains exhibited remarkable resilience against bile, NaCl, and SPJ, as well as susceptibility to antibiotics and antagonistic behavior against pathogens. These strains also showed the presence of β-D-galactosidase. Additionally, five L. plantarum strains were found to harbor the gad gene. Further biochemical analysis of four specific L. plantarum strains revealed promising profiles consisting of antibiotics, vitamins, hormones, and a diverse array of metabolites with potential immunotherapeutic properties. This study highlights the substantial potential of Lactiplantibacillus plantarum in generating beneficial postbiotic metabolites. The identified strains offer exciting avenues for further exploration, with potential applications in functional foods and pharmaceuticals. This research opens up possibilities for harnessing the probiotic and postbiotic potential of L. plantarum to develop novel products with health-promoting properties. [ABSTRACT FROM AUTHOR]

Sheet-to-cloud cavitation in a Venturi pipe is investigated experimentally and numerically in this work. The multiscale vapor structures are simulated by Eulerian–Lagrangian multiscale modeling. The volume of fluid method with adaptive mesh refinement is employed to capture the macroscale cavity features, utilizing the large eddy simulation approach. The results of mesh sensitivity study demonstrate that second-order refinement is capable of capturing phase details and cavitation shedding behaviors. A comparison with experimental results reveals the mechanisms of different types of cavitation shedding induced by reentrant jet and shock wave. Taking microscale bubbles into account using the Lagrangian approach and achieving Eulerian–Lagrangian coupling, the multiscale cavitation features, including the morphological evolution of large cavities and characteristics of microbubbles, are accurately reproduced. The evolution features of microbubbles during pressure wave or condensation shock propagation are well recognized by different changing rates. The results indicate that shedding mechanisms in Venturi pipe cavitation can be categorized into three types: reentrant jet, condensation shock, and pressure wave. In the three conditions investigated in this work, shedding cycles are found to be mainly induced by the reentrant jet (σ = 1.03), reentrant jet, condensation shock, and pressure wave (σ = 0.64), and condensation shock (σ = 0.39), respectively, with a decrease in the cavitation number. [ABSTRACT FROM AUTHOR]

In the field of magnetic anomaly detection (MAD), the anomaly signal is easily submerged by ambient electromagnetic interference. Though the existing noise suppression methods can effectively improve the signal-to-noise ratio (SNR), there are still some intractable problems, such as signal distortion and boundary blur. To solve these problems, a novel MAD method based on structured low rank (SLR) and total variation (TV) regularization constraints is proposed in this letter. The noise suppression performance is improved by leveraging the structured low rankness of the signal. To preserve clean boundaries of the anomalies, an anisotropic TV regularization constraint is employed in the approach. Comparing the SLR-TV method with four state-of-the-art methods with extensive field tests, the results demonstrate that the proposed SLR-TV method achieves the greatest SNR improvement by about 63.24% and the best structural similarity (SSIM) improvement by about 53.02% over other methods in the range from −40 to 0 dB, showing the utility and high fidelity of the proposed framework in low SNR. [ABSTRACT FROM AUTHOR]

Mannosylerythritol lipids-A (MEL-A) is a novel biosurfactant with multiple biological effects. The synergistic antibacterial activity and mechanism of MEL-A and lactic acid (LA) against Listeria monocytogenes were investigated. The synergistic effect resulted in a significant increase in the antibacterial rate compared to LA treatment alone. Genome-wide transcriptomic analysis was applied to deeply investigate the synergistic antibacterial mechanism. Gene Ontology (GO) enrichment analysis showed that the synergy between MEL-A and LA affected many potential cellular responses, including the sugar phosphotransferase system, carbohydrate transport, and ribosomes. KEGG enrichment analysis showed that the PTS system and ribosome-related pathways were significantly enriched. In addition, synergistic treatment affected locomotion and membrane-related cellular responses in GO enrichment analysis and carbohydrate metabolism and amino acid metabolism pathways in KEGG enrichment analysis compared to LA treatment alone. The accuracy of the transcriptome analysis results was verified by qPCR (R2 = 0.9903). This study will provide new insights for the prevention and control of L. monocytogenes. [ABSTRACT FROM AUTHOR]

Objective. To investigate hypoxia-induced Nestin regulates lung cancer viability and metabolism by targeting transcription factors Nrf2, STAT3, and SOX2. Methods. Eighty-four cases of nonsmall cell lung cancer (nonsmall cell lung cancer, NSCLC), which had been treated from June 2020 to February 2021, were randomly selected from our clinicopathology database. Immunohistochemical staining of collected tissue cells was performed to assess the expression patterns of Nestin, STAT3, Nrf2, and SOX2. Data were quantified and statistically analyzed using one-way and two-way ANOVA tests with P < 0.05. Results. Clinicopathological findings showed significant differences in lymph node metastasis, tissue differentiation, and histology on induction of Nestin expression; Nestin expression correlated with STAT3, Nrf2, and SOX2 expression.Nestin/STAT3/SOX2/Nrf2 are involved in angiogenesis and lung cancer development. Conclusion. Hypoxia-induced Nestin promotes the progression of nonsmall lung cancer cells by targeting the downstream transcription factors STAT3, Nrf2, and SOX2. [ABSTRACT FROM AUTHOR]

Users can invoke various composite services in Edge Computing (EC) with the development of Service Computing. Generally, users cannot invoke the optimal composite service due to the migration of component service or failure in the edge device. In this study, a Composite Service Provisioning mechanism in EC (CSP-EC) is proposed. It starts when the location of component service changes and terminates when the optimal composite service is obtained. CSP-EC employs dynamic optimization process to meet the real-time requirements. It first caches m optimized intermediate solutions from the first m users, which can be reused by other users to get the final optimal solution. Moreover, a multipopulation Estimation of Distribution Algorithm is used to reduce the probability of falling into a local optimum, and the roulette mechanism is used to accelerate the optimization process. Extensive simulations are conducted based on the real-world dataset. The results show that the proposed mechanism achieves higher quality, better stability, and shorter execution time compared with other schemes. [ABSTRACT FROM AUTHOR]

Reverse auction-based incentive mechanisms have been widely adopted to stimulate mobile workers to participate in mobile crowdsensing (MCS), where workers need to provide location information for winner selection. However, most existing mechanisms rely on trusted platforms. The worker’s location data uploaded to platforms thus can be easily exposed. Recent works start to incorporate location privacy in designing incentive mechanisms, but they have not considered the task’s location privacy and the worker’s location privacy simultaneously. Therefore, we propose a bilateral location privacy-preserving mechanism for MCS on untrusted platforms. In our model, each worker adopts differential privacy to obfuscate his location locally and then submits the obfuscated location together with the bid information. Besides, instead of the exact location, the task requester is only required to upload the task profile and the task’s obfuscated location. Then, we propose the lowest-cost winner selection mechanism which aims to minimize the social cost of winner selection under the location constraint while ensuring task quality requirements, and adopt the critical payment determination mechanism to determine the payments for the winners, which satisfies truthfulness, individual rationality, and computational efficiency. Theoretical analysis and extensive experiments on real-world datasets show the effectiveness of the proposed mechanisms. [ABSTRACT FROM AUTHOR]

The magnetic anomalies generated by the ferromagnetic targets are usually buried within uncontrollable interference sources, such as the power frequency and random noises. In particular, the variability of the geomagnetic field and the low signal-to-noise ratio (SNR) of the magnetic anomalies cannot be avoided. In this paper, to improve the performance of magnetic anomaly detection (MAD) with a low SNR, we propose a novel structured low-rank (SLR) decomposition-based MAD method. In addition, a new framework based on the SLR and singular value decomposition (SVD) is constructed, dubbed SLR-SVD, and the corresponding working principle and implemented strategy are elaborated. Through comparing the SLR-SVD with two state-of-the-art methods, including principal component analysis and SVD, the results demonstrate that the proposed SLR-SVD can not only suppress the noise sufficiently, i.e., improving 55.26% approximately of the SNR, but also retain more boundary information of magnetic anomalies, i.e., decreasing approximately 68.05% of the mean squared error and improving approximately 28.47% of the structural similarity index. [ABSTRACT FROM AUTHOR]

Enterococci, a type of lactic acid bacteria, are widely distributed in various environments and are part of the normal flora in the intestinal tract of humans and animals. Although enterococci have gradually evolved pathogenic strains causing nosocomial infections in recent years, the non-pathogenic strains have still been widely used as probiotics and feed additives. Enterococcus can produce enterocin, which are bacteriocins considered as ribosomal peptides that kill or inhibit the growth of other microorganisms. This paper reviews the classification, synthesis, antibacterial mechanisms and applications of enterocins, and discusses the prospects for future research. [ABSTRACT FROM AUTHOR]

The minimum travel distance of task participants is one of the significant optimization objectives of privacy-preserving task assignment in mobile crowdsensing (MCS). However, when the travel distance is minimized, most of the previous schemes only focus on the task participant privacy and disregard the task requester privacy. Moreover, existing solutions usually only support the constraint of a single type, such as equality constraints or range constraints. In this paper, we propose a bilateral privacy-preserving Task Assignment mechanism for MCS (iTAM), which protects not only the task participants privacy but also the task requesters privacy and can minimize the travel distance. Furthermore, iTAM provides both equality and range constraints of task assignment by utilizing the Paillier cryptosystem. To accommodate the multiple relations between the task participants and the task, we propose the single/multiple task participants selection problems for a task requiring task participants to compete and cooperate. Experimental evaluations over synthetic and real-world data illustrate that iTAM is feasible and effective. Compared with the state-of-the-art, iTAM positively solves the optimal problem of travel distance. The complexities of iTAM are $\mathcal {O}(n)$ O (n) and $\mathcal {O}(n\log n)$ O (n log n) for a single and multiple task participants selection problems, respectively. [ABSTRACT FROM AUTHOR]

Task assignment is a critical issue in mobile crowdsensing (MCS), an emerging sensing paradigm applied to realize various sensing applications for smart cities. Existing task assignment schemes mostly require the exact location information of tasks and workers for optimization, which inevitably brings the issue of location privacy leakage. Therefore, researchers have started investigating privacy-preserving task assignment schemes. However, most of these works either make inaccurate assignments or only concentrate on workers’ privacy. In this article, we propose a novel bilateral privacy-preserving and accurate task assignment framework in fog-assisted MCS, called BRAKE. Specifically, we utilize the multisecret sharing scheme to preserve location privacy in the MCS task assignment, where tasks and workers only need to provide the secret shares of their real location information to fog nodes. Moreover, we consider distance-oriented and time-oriented tasks for assignment optimization and propose an adaptive top-k worker selection algorithm to accurately select the most suitable workers. The security analysis proves that BRAKE can resist collusion attacks, and the extensive evaluation results demonstrate the efficiency and accuracy of BRAKE. [ABSTRACT FROM AUTHOR]

SUMMARY: Root growth relies on both cell division and cell elongation, which occur in the meristem and elongation zones, respectively. SCARECROW (SCR) and SHORT‐ROOT (SHR) are GRAS family genes essential for root growth and radial patterning in the Arabidopsis root. Previous studies showed that SCR and SHR promote root growth by suppressing cytokinin response in the meristem, but there is evidence that SCR expressed beyond the meristem is also required for root growth. Here we report a previously unknown role for SCR in promoting cell elongation. Consistent with this, we found that the scr mutant accumulated a higher level of reactive oxygen species (ROS) in the elongation zone, which is probably due to decreased expression of peroxidase gene 3, which consumes hydrogen peroxide in a reaction leading to Casparian strip formation. When the oxidative stress response was blocked in the scr mutant by mutation in ABSCISIC ACID 2 (ABA2) or when the redox status was ameliorated by the upbeat 1 (upb1) mutant, the root became significantly longer, with longer cells and a larger and more mitotically active meristem. Remarkably, however, the stem cell and radial patterning defects in the double mutants still persisted. Since ROS and peroxidases are essential for endodermal differentiation, these results suggest that SCR plays a role in coordinating cell elongation, endodermal differentiation, redox homeostasis and oxidative stress response in the root. We also provide evidence that this role of SCR is independent of SHR, even though they function similarly in other aspects of root growth and development. [ABSTRACT FROM AUTHOR]

In aeromagnetic surveys, poor aircraft heading and weather may frequently cause a classical optically-pumped sensor to enter into or close to its dead zone, which results in unavoidable outliers that seriously reduce aeromagnetic compensation. To address these problems, a method to identify rapidly and pre-cull magnetic outliers based on the gray system theory is proposed to reduce their negative influence during the estimation of coefficients and target detection robustness. By constructing a gray region of aeromagnetic data and then checking whether the data at the end points of the region are normal, aeromagnetic outliers can be culled. The simulation results show that even if the outlier rate is increased to 20%, the average of the correct culling rate of the proposed method can still reach 99.67%, at which the culling effect is highly robust. We constructed an experimental survey platform and conducted a flight test. The results show that the improvement ratio of the proposed method can reach 4.36, which is 10.38 times higher than the conventional method. [ABSTRACT FROM AUTHOR]

Providing appropriate monetary rewards is an efficient way for mobile crowdsensing to motivate the participation of task participants. However, a monetary incentive mechanism is generally challenging to prevent malicious task participants and a dishonest task requester. Moreover, prior quality-aware incentive schemes are usually failed to preserve the privacy of task participants. Meanwhile, most existing privacy-preserving incentive schemes ignore the data quality of task participants. To tackle these issues, we propose a privacy-preserving and data quality-aware incentive scheme, called PACE. In particular, data quality consists of the reliability and deviation of data. Specifically, we first propose a zero-knowledge model of data reliability estimation that can protect data privacy while assessing data reliability. Then, we quantify the data quality based on the deviation between reliable data and the ground truth. Finally, we distribute monetary rewards to task participants according to their data quality. To demonstrate the effectiveness and efficiency of PACE, we evaluate it in a real-world dataset. The evaluation and analysis results show that PACE can prevent malicious behaviors of task participants and a task requester, and achieves both privacy-preserving and data quality measurement of task participants. [ABSTRACT FROM AUTHOR]

Mobile crowdsensing (MCS) is a popular paradigm to collect sensed data for numerous sensing applications. With the increment of tasks and workers in MCS, it has become indispensable to design efficient task allocation schemes to achieve high performance for MCS applications. Many existing works on task allocation focus on single-task allocation, which is inefficient in many MCS scenarios where workers are able to undertake multiple tasks. On the other hand, many tasks are time-limited, while the available time of workers is also limited. Therefore, time validity is essential for both tasks and workers. To accommodate these challenges, this paper proposes a multi-task allocation problem with time constraints, which investigates the impact of time constraints to multi-task allocation and aims to maximize the utility of the MCS platform. We first prove that this problem is NP-complete. Then two evolutionary algorithms are designed to solve this problem. Finally, we conduct the experiments based on synthetic and real-world datasets under different experiment settings. The results verify that the proposed algorithms achieve more competitive and stable performance compared with baseline algorithms. [ABSTRACT FROM AUTHOR]

To study the effect of fine particle size and volume concentration on the performance of solid-liquid two-phase centrifugal pump, the mixture multiphase flow model, RNG k-ε turbulence model, and SIMPLEC algorithm were used to simulate the two-phase flow of the centrifugal pump. The effects of particle size and volume concentration on internal pressure distribution, solid volume distribution, and external characteristics were analyzed. The results show that under the design discharge conditions, with the increase of particle size and volume concentration, the internal pressure of the flow field will decrease, and the volume fraction of solid phase in the impeller passage will also decrease as a whole. The solid particles gradually migrate from the suction surface to the pressure surface, and the particles in the volute channel are mainly concentrated in the flow channel near the outlet side of the volute. With the increase of particle size and volume concentration, the negative pressure value at the inlet of centrifugal pump increases, the total pressure difference at the inlet and outlet decreases, and the head and efficiency decrease accordingly. [ABSTRACT FROM AUTHOR]

The traditional aeromagnetic compensation model does not consider the negative effects of the gradient of the geomagnetic background field. Especially in emergency aeromagnetic surveys, this gradient effect is obvious and can reduce the performance of magnetic compensation. To solve this problem, we propose a method of reducing the gradient effect of the magnetic sensor for aeromagnetic compensation. A magnetic gradient model of the Earth's background field is established for the aeromagnetic compensation, and the gradient effect is then suppressed using altitude data. An experimental platform was built, and flight tests were conducted. Comparison results show that the adoption of the proposed method increased the improvement ratio (IR) of our compensator on two flights from 20.4 and 21.3 to 25.9 and 26.0, with the growth rates of the IR, respectively, reaching 27% and 22%. [ABSTRACT FROM AUTHOR]

The gear transmission system is widely used in high-speed centrifugal pump to improve the operating speed and hydraulic performances of the whole pump. Vibration characteristics and the stability of these high-speed rotor systems with gear transmission have great impacts on the stability of the whole fluid transmission system of the plant. Based on the lumped-mass method and the principle of displacement equilibrium of the rotor system, a coupled lateral-torsional dynamic model describing the gear-rotor-seal-bearing (GRSB) system of high-speed centrifugal pumps which has considered the nonlinear factors within the gear pair, nonlinear forces of bearings, and those of the seals is proposed. Then, the stability and nonlinear vibration responses of a model GRSB system under different gear transmission ratios (i) have been studied. The following conclusions are drawn from the results: (1) The components with frequencies like fp, f g , fm, and 2fm have great impacts on the vibration responses of the gear pair, especially the fm component; moreover, the amplitude of fm first increases and then decreases with the ratio increase and reaches the maximum value under the ratio of 3. (2) A jump motion state will occur when the ratio i is 1.25 and the stability of the system is obviously worse than the bifurcation state. Quite different from those under the other states, under this jump motion state, the 0.2 f g component and 0.5fp component will appear in the vibration responses of both gears and become the most contributed two factors to the responses of the driven gear. (3) In the design process, the transmission ratio of a high-speed centrifugal pump with a simplified GRSB system should be specially designed to avoid the jump-point state and the maximum-amplitude-of-fm state to ensure the stability of the system as well as reduce the mechanical impacts and noises. [ABSTRACT FROM AUTHOR]

Accurate forecast of citywide crowd flows on flexible region partition benefits urban planning, traffic management, and public safety. Previous research either fails to capture the complex spatiotemporal dependencies of crowd flows or is restricted on grid region partition that loses semantic context. In this paper, we propose DeepFlowFlex, a graph-based model to jointly predict inflows and outflows for each region of arbitrary shape and size in a city. Analysis on cellular datasets covering 2.4 million users in China reveals dependencies and distinctive patterns of crowd flows in not only the conventional space and time domains, but also the speed domain, due to the diverse transportation modes in the mobility data. DeepFlowFlex explicitly groups crowd flows with respect to speed and time, and combines graph convolutional long short-term memory networks and graph convolutional neural networks to extract complex spatiotemporal dependencies, especially long-term and long-distance inter-region dependencies. Evaluations on two big cellular datasets and public GPS trace datasets show that DeepFlowFlex outperforms the state-of-the-art deep learning and big-data-based methods on both grid and non-grid city map partition. [ABSTRACT FROM AUTHOR]