In-field fuel use and load states of agricultural field machinery

The ability to define in-field tractor load states offers the potential to better specify and characterize fuel consumption rate for various field operations. For the same field operation, the tractor experiences diverse load demands and corresponding fuel use rates as it maneuvers through straight passes, turns, suspended operation for adjustments, repair and maintenance, and biomass or other material transfer operations. It is challenging to determine the actual fuel rate and load states of agricultural machinery using force prediction models, and hence, some form of in-field data acquisition capability is required. Controller Area Networks (CAN) available on the current model tractors provide engine performance data which can be used to determine tractor load states in field conditions. In this study, CAN message data containing fuel rate, engine speed and percent torque were logged from the tractor’s diagnostic port during anhydrous NH3 application, field cultivation and planting operations. Time series and frequency plots of fuel rate and percent torque were generated to evaluate tractor load states. Based on the percent torque, engine speed and rated engine power, actual load on the tractor was calculated in each tractor load state. Anhydrous NH3 application and field cultivation were characterized by three distinct tractor load states (TS-I, TS-II and TS-III) corresponding to idle states, parallel and headland passes, and turns, whereas corn planting was characterized by two load states (TS-I and TS-II): idle, and a combined state with parallel, headland passes and turns. For anhydrous NH3 application and field cultivation at ground speeds of 7.64 km h–1 and 8.68 km h–1, average tractor load per tool and fuel use rate per tool of the implement were found to be 7.21 kW tool–1, 3.28 L h–1 tool–1, and 1.31 kW tool–1, 0.64 L h–1 tool–1, respectively. For planting, average tractor load per row and fuel use rate per row were found to be 4.65 kW row–1 and 1.70 L h–1 row–1 at a ground speed of 7.04 km h–1

A Robust Optimization Approach to Public Transit Mobile Real-time Information

In the past few years, numerous mobile applications have made it possible for public transit passengers to find routes and learn about the expected arrival times of their transit vehicles. Previous studies show that provision of accurate real-time bus information is vital to passengers for reducing their anxieties and wait times at bus stops. Inadequate and/or inaccurate real-time information not only confuses passengers but also reinforces the bad image of public transit. However, almost all methods of real-time information optimization are aimed at predicting bus arrival or travel times. In order to make up for the lack of information accuracy, this paper proposes a new approach to optimize mobile real-time information for each transit route based on robust linear optimization. An error estimation is added to current bus arrival time information as a new element of mobile bus applications. The proof process of the robust optimization model is also presented in this paper. In the end, the model is tested on two comparable bus routes in Shanghai. The real-time information for these two routes was obtained from Shanghai Bus, a mobile application used in  Shanghai City. The test results reflect the validity, disadvantages, and risk costs of the model

PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow

This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single lightweight framework. We name it PRO-Face S, short for Privacy-preserving Reversible Obfuscation of Face images via Secure flow-based model. In the framework, an Invertible Neural Network (INN) is utilized to process the input image along with its pre-obfuscated form, and generate the privacy protected image that visually approximates to the pre-obfuscated one, thus ensuring privacy. The pre-obfuscation applied can be in diversified form with different strengths and styles specified by users. Along protection, a secret key is injected into the network such that the original image can only be recovered from the protection image via the same model given the correct key provided. Two modes of image recovery are devised to deal with malicious recovery attempts in different scenarios. Finally, extensive experiments conducted on three public image datasets demonstrate the superiority of the proposed framework over multiple state-of-the-art approaches

Multiscale structural disorganization of indica rice starch under microwave treatment with high water contents

While the cooking of rice into porridge or similar foods is widely practiced, how microwave treatment, a rapid heating technology, changes the structure of rice starch with excess water remains largely unexplored. This work describes the multiscale structural changes of indica rice starch (IRS) with high water contents (70, 80, and 90 wt %, wet basis) subjected to microwave treatment for 1–3 min. Microwave treatment destructed crystalline lamellae, changed the crystalline type from A to B+V, and decreased crystallinity and double-helix content. While these changes depend on both water content and treatment time, the former had a stronger effect due to combined effects of water and heat for starch gelatinization. Interestingly, a highly porous material can be obtained simply upon microwave treatment of IRS for 3 min at a water content of 90 wt %. Thus, this work presents a simple method for creating such material promising for encapsulation and delivery applications

A humification-based method toward refining Holocene radiocarbon chronologies: Wetland records from southeastern China

Holocene paleoclimate reconstructions and comparisons largely rely on accurate age-depth modeling. However, uncertainties in chronology, such as those caused by sparse radiocarbon dates, will hamper inter-core comparisons and correlations, and might result in misleading “cause and consequence” conclusions. This study aimed to find a solution to increase the comparability and minimize the uncertainty of wetland chronology as much as possible. Sediment cores were recovered and radiocarbon dated from the Lianhuachi wetland located in Southeastern China. Humification degree and loss-on-ignition (LOI) were determined using colorimetric and combustion methods respectively. Our data were compared with previously published datasets obtained in the same wetland. The results show that independent humification profiles from the Lianhuachi wetland displayed high similarities. This high similarity between the humification profiles allowed us to transfer radiocarbon ages from one core to another using sequence slotting correlation. Applying the humification-based chronology refinement method to all sediment cores resulted in an improvement in the correlation coefficients between the same but independently measured proxy sequences from the wetland, which suggests both the inter- and intra-core comparability was improved. Because determining peat humification degree is easy, inexpensive, and time-saving, we suggest that humification can serve as a tool that can be used to correlate different cores and to transfer published radiocarbon ages within the same wetland (peatland) or in a comparable geological setting, to establish a more robust chronology of these comparable cores. The degree of peat humification can thus serve as a relative dating technique to refine the chronology of wetland (including peatland) records

Dependence of Chemical Abundance on the Cosmic Ray Ionization Rate in IC 348

Ions (e.g., H$_3^+$, H$_2$O$^+$) have been used extensively to quantify the cosmic-ray ionization rate (CRIR) in diffuse sightlines. However, measurements of CRIR in low-to-intermediate density gas environments are rare, especially when background stars are absent. In this work, we combine molecular line observations of CO, OH, CH, and HCO$^+$ in the star-forming cloud IC~348, and chemical models to constrain the value of CRIR and study the response of the chemical abundances distribution. The cloud boundary is found to have an $A_{\rm V}$ of approximately 4 mag. From the interior to the exterior of the cloud, the observed $^{13}$CO line intensities drop by an order of magnitude. The calculated average abundance of $^{12}$CO (assuming $^{12}$C/$^{13}$C = 65) is (1.2$\pm$0.9) $\times$10$^{-4}$, which increases by a factor of 6 from the interior to the outside regions. The average abundance of CH (3.3$\pm$0.7 $\times$ 10$^{-8}$) is in good agreement with previous findings in diffuse and translucent clouds ($A_{\rm V}$ $<$ 5 mag). However, we did not find a decline in CH abundance in regions of high extinction ($A_{\rm V}\simeq$8 mag) as previously reported in Taurus. By comparing the observed molecular abundances and chemical models, we find a decreasing trend of CRIR as $A_{\rm V}$ increases. The inferred CRIR of $\zeta_{cr}$ = (4.7$\pm$1.5) $\times$ 10$^{-16}$ s$^{-1}$ at low $A_{\rm V}$ is consistent with H$^+_3$ measurements toward two nearby massive stars.Comment: 21 pages, 11 figures. Submitted to Ap

Oral Probiotics Ameliorate the Behavioral Deficits Induced by Chronic Mild Stress in Mice via the Gut Microbiota-Inflammation Axis

In recent years, a burgeoning body of research has revealed links between depression and the gut microbiota, leading to the therapeutic use of probiotics for stress-related disorders. In this study, we explored the potential antidepressant efficacy of a multi-strain probiotics treatment (Lactobacillus helveticus R0052, Lactobacillus plantarum R1012, and Bifidobacterium longum R0175) in a chronic mild stress (CMS) mouse model of depression and determined its probable mechanism of action. Our findings revealed that mice subjected to CMS exhibited anxiety- and depressive-like behaviors in the sucrose preference test, elevated plus maze, and forced swim test, along with increased interferon-γ, tumor necrosis factor-α, and indoleamine 2,3-dioxygenase-1 levels in the hippocampus. Moreover, the microbiota distinctly changed from the non-stress group and was characterized by highly diverse bacterial communities associated with significant reductions in Lactobacillus species. Probiotics attenuated CMS-induced anxiety- and depressive-like behaviors, significantly increased Lactobacillus abundance, and reversed the CMS-induced immune changes in the hippocampus. Thus, the possible mechanism involved in the antidepressant-like activity of probiotics is correlated with Lactobacillus species via the gut microbiota-inflammation-brain axis