Comparison of mesophilic and thermophilic anaerobic digestions of thermal hydrolysis pretreated swine manure: Process performance,microbial communities and energy balance

Anaerobic digestion (AD) of swine manure (SM) commonly shows low biogas output and unsatisfactory economic performance. In this study, thermophilic AD (TAD, 50±1℃) was combined with thermal hydrolysis pretreatment (THP, 170℃/10 bar), to investigate its potential for maximizing biogas yield, securing successful digestion and microbial diversity, as well as improving energy balance. Four lab-scale continuously stirred tank reactors were operated for 300 days and compared with each other, i.e., reactor 1 (raw SM fed in mesophilic AD:RSM-MAD), reactor 2 (THP-treated SM fed in MAD:TSM-MAD), reactor 3 (RSM-TAD),and reactor 4 (TSM-TAD). The results showed that THP was efficient to increase methane production of SM, TSM-TAD mode led to the highest methane yield (129.8±40.5 mL-CH_(4)/gVS/day) among the tests (p <0.05). Although TAD was more likely to induce free ammonia (> 700 mg/L) or volatile fatty acids (> 6000 mg/L) accumulation compared with MAD in start-up phase, TSM-TAD treatment mode behaved a sustainable digestion process in a long-term operation. For TSM-TAD scenario, higher Shannon–Weaver (3.873) and lower Simpson index (0.061) indicated this mode ensured and enlarged the diversity of bacteria communities. Phylum Bathyarchaeota was dominant (59.3%-90.0%) in archaea community,followed by Euryarchaeota in the four reactors. RSM-MAD treatment mode achieved the highest energy output (4.65 GJ/day), TSM-TAD was less effective (-17.38 GJ/day) due to increased energy demands. Thus improving the energetic efficiency of THP units is recommended for the development of TSM-TAD treatment mode.

Process performance and quality attributes of temperature and step-down relative humidity controlled hot air drying of Panax notoginseng roots

The effects of temperature and step-down relative humidity controlled hot-air drying(THC-HAD)on the drying kinetics,energy efficiency and quality,i.e.,rehydration ratio(RR),color parameters(L*,a*,b*),total color difference(ΔE*),Panax notoginseng saponins(PNS)content,and ginsenosides content(R1,Rg1,Re,Rd,Rb1)of Panax notoginseng roots were evaluated.The drying time was significantly affected by the drying temperature followed by the relative humidity(RH)of the drying air.Special combination of drying conditions,i.e.,drying temperature of 50°C,relative humidity of 40%for 3 h and then continuous dehumidification from 40%to 8%allowed to shorten the drying time by 25%compared to drying at the same temperature and continuous dehumidification.The longer was the drying time under constant high RH of drying air,the lower was the RR of dried samples.The step-down RH strategy contributed to the formation of a porous structure,enhancement of drying efficiency and quality improvement.Generally,the ginsenosides content increased with the increase in temperature,while no obvious trend was recorded for ginsenoside R1.The contents of the ginsenoside R1,Rg1,Rb1 and PNS decreased with the increase in the drying time under constant high RH.Taking into account the drying time,energy consumption and quality attributes,drying at the temperature of 50°C,constant RH of 40%for 3 h and then step-down RH from 40%to 8%was proposed as the most favorable combination of drying conditions for dehydration of whole Panax notoginseng roots.

Effects of Post-expanding Lower Temperature Granulating Process on Growth Performance of Piglets

[Objective] The paper was to compare the effects of traditional granulating process and post-expanding lower temperature granulating process on starch gelatinization degree and in vitro protein digestibility of conversation feed, and growth performance of piglets. [Method] Sixty weaned piglets, 25 days old, were randomly divided into two groups, six replicates each group, and each replicate contained five piglets. Piglets in control group were fed with the conversation feed developed by traditional granulating process, and those in experimental group were fed with the conservation feed developed by post-expanding lower temperature granulating process. The trial lasted 28 d. [Result] Compared to traditional granulating process, post-expanding lower temperature granulating process significantly enhanced starch gelatinization degree of conservation feed by56.9%（P〈0.05）, and significantly improved in vitro protein digestibility of conservation feed by 11.48%（P〈0.05）. Compared to the control group, the feed intake of piglets in experimental group was increased by 21.63%（P〈0.05）; the average daily gain was increased by 27.61%（P〈0.05）; the diarrhea rate was lowered; and the feed gain ratio was improved by 4.51%（P〉0.05）. The results suggested that post-expanding lower temperature granulating process effectively enhanced feed digestion and absorption of piglets. [Conclusion] The paper provides a theoretical basis and practical reference for improvement of production process of conservation feed.

Applying Analytical Hierarchy Process to a WiMAX Performance Evaluation Model

Evaluating performance of individual features of WiMAX technology is a topic of widespread discussion. Currently, there is no quantitative way of measuring WiMAX technology so that wireless operators can meet their design objectives. This paper outlines a set of design criteria for WiMAX and provides a decision-making aid that ranks the importance of criteria using Analytic Hierarchy Process （AHP）. This ranking should sufficiently reflect market expectations of the relative importance of various design criteria. A model integrating AHP priorities with enhanced Data Envelopment Analysis （DEA） is the basis for formulating a technological value in simple, comparable format. A case study is provided to show how this technological value is used to evaluate a three year network deployment plan. In the future, this model could be extended to WiMAX equipment suppliers for the purpose of validating performance targets of individual criteria, and enhancing supplier roadmaps for future network development.

G-forward performance process and representation of homothetic case via ergodic quadratic G-BSDE

We introduce a new type of robust forward criterion under model uncertainty,called the G-forward performance process,which extends the classical notion of forward performance process to the G-expectation framework.We then derive the representations of homothetic G-forward performance processes in a single stochastic factor model with uncertainty,building on the well-posedness of ergodic and infinite horizon backward stochastic differential equations driven by G-Brownian motion(G-BSDEs)with quadratic generators.

A Review on Ultrasonic-Assisted Forming:Mechanism,Model,and Process

Compared with conventional forming processes,ultrasonic-assisted forming technology with a high frequency and small amplitude can significantly improve the forming quality of materials.Owing to the advantages of reduced forming force,improved surface quality,avoidance of forming defects,and strengthened surface structure,ultrasonic-assisted forming technology has been applied to increasingly advanced forming processes,such as incremental forming,spinning,and micro-forming.However,in the ultrasonic-assisted forming process,there are multiple ultrasonic mechanisms,such as the volume effect and surface effect.The explanation of the effect of ultrasonic vibration(UV)on plastic deformation remains controversial,hindering the development of related technologies.Recently,many researchers have proposed many new theories and technologies for ultrasonic-assisted forming.To summarize these developments,systematic discussions on mechanisms,theoretical models,and forming performances are provided in this review.On this basis,the limitations of the current study are discussed.In addition,an outlook for ultrasonic-assisted forming is proposed:efficient and stable UV systems,difficulty forming components with complex geometry,explanation of the in-depth mechanism,a systematic theoretical prediction model,and multi-field-coupling energy-assisted forming are considered to be hot spots in future studies.The present review enhances existing knowledge of ultrasonic-assisted forming,and facilitates a fast reference for related researchers.

Approximate-model Based Estimation Method for Dynamic Response of Forging Processes

Many high-quality forging productions require the large-sized hydraulic press machine（HPM） to have a desirable dynamic response. Since the forging process is complex under the low velocity, its response is difficult to estimate. And this often causes the desirable low-velocity forging condition difficult to obtain. So far little work has been found to estimate the dynamic response of the forging process under low velocity. In this paper, an approximate-model based estimation method is proposed to estimate the dynamic response of the forging process under low velocity. First, an approximate model is developed to represent the forging process of this complex HPM around the low-velocity working point. Under guaranteeing the modeling performance, the model may greatly ease the complexity of the subsequent estimation of the dynamic response because it has a good linear structure. On this basis, the dynamic response is estimated and the conditions for stability, vibration, and creep are derived according to the solution of the velocity. All these analytical results are further verified by both simulations and experiment. In the simulation verification for modeling, the original movement model and the derived approximate model always have the same dynamic responses with very small approximate error. The simulations and experiment finally demonstrate and test the effectiveness of the derived conditions for stability, vibration, and creep, and these conditions will benefit both the prediction of the dynamic response of the forging process and the design of the controller for the high-quality forging. The proposed method is an effective solution to achieve the desirable low-velocity forging condition.

Effects of Calcium Lignosulfonate(CaLS)on Growth Performance,Slaughter Performance and Antioxidant Function of Meat Duck

[Objective]The paper was to study the effects of calcium lignosulfonate(CaLS)on feed processing performance,growth performance,slaughter performance and antioxidant function of cherry valley duck.[Method]A total of 48010-day-old cherry valley ducks were selected and randomly divided into four treatments,10 replicates each treatment and 12 meat ducks each replicate(half male and half female).The ducks in control group were fed with basal diet,and those in experimental groups were fed with the basal diet adding 0.2%,0.4%and 0.6%CaLS,respetively.The trial lasted 28 d.[Result](1)CaLS significantly reduced feed pulverization rate of meat duck(F<0.05),and significantly increased PDI and starch gelatinization degree(F<0.05);adding CaLS had no significant impact on the processing cost(F>0.05),but the granulation electric charge per ton feed could be reduced by 1.06 yuan.(2)CaLS had no significant effect on growth performance,slaughter performance and organ index of meat duck(Q0.05).(3)Compared with the control group,there were no significant differences in serum GSH-Px,T-SOD,T-AOC activities and MDA content of three CaLS groups(F>0.05).[Conclusion]CaLS could improve the processing quality of meat duck feed and reduce the processing cost,hut could not improve the growth performance,slaughter performance and antioxidant function of meat duck.

Predictable forward performance processes in complete markets

We establish existence of Predictable Forward Performance Processes(PFPPs)in conditionally complete markets,which has been previously shown only in the binomial setting.Our market model can be a discrete-time or a continuous-time model,and the investment horizon can be finite or infinite.We show that the main step in construction of PFPPs is solving a one-period problem involving an integral equation,which is the counterpart of the functional equation found in the binomial case.Although this integral equation has been partially studied in the existing literature,we provide a new solution method using the Fourier transform for tempered distributions.We also provide closedform solutions for PFPPs with inverse marginal functions that are completely monotonic and establish uniqueness of PFPPs within this class.We apply our results to two special cases.The first one is the binomial market and is included to relate our work to the existing literature.The second example considers a generalized Black–Scholes model which,to the best of our knowledge,is a new result.

A Multi-Task Motion Generation Model that Fuses a Discriminator and a Generator

The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spatial-temporal structures,and the deep learning model can fully describe the potential semantic structure of human motion.To improve the authenticity of the generated human motion sequences,we propose a multi-task motion generation model that consists of a discriminator and a generator.The discriminator classifies motion sequences into different styles according to their similarity to the mean spatial-temporal templates from motion sequences of 17 crucial human joints in three-freedom degrees.And target motion sequences are created with these styles by the generator.Unlike traditional related works,our model can handle multiple tasks,such as identifying styles and generating data.In addition,by extracting 17 crucial joints from 29 human joints,our model avoids data redundancy and improves the accuracy of model recognition.The experimental results show that the discriminator of the model can effectively recognize diversified movements,and the generated data can correctly fit the actual data.The combination of discriminator and generator solves the problem of low reuse rate of motion data,and the generated motion sequences are more suitable for actual movement.

Forward robust portfolio selection: The binomial case

We introduce a new approach for optimal portfolio choice under model ambiguity by incorporating predictable forward preferences in the framework of Angoshtari et al.[2].The investor reassesses and revises the model ambiguity set incrementally in time while,also,updating his risk preferences forward in time.This dynamic alignment of preferences and ambiguity updating results in time-consistent policies and provides a richer,more accurate learning setting.For each investment period,the investor solves a worst-case portfolio optimization over possible market models,which are represented via a Wasserstein neighborhood centered at a binomial distribution.Duality methods from Gao and Kleywegt[10];Blanchet and Murthy[8]are used to solve the optimization problem over a suitable set of measures,yielding an explicit optimal portfolio in the linear case.We analyze the case of linear and quadratic utilities,and provide numerical results.

Exploiting big earth data from space - first experiences with the timescan processing chain

The European Sentinel missions and the latest generation of the United States Landsat satellites provide new opportunities for global environmental monitoring.They acquire imagery at spatial resolutions between 10 and 60 m in a temporal and spatial coverage that could before only be realized on the basis of lower resolution Earth observation data(>250 m).However,images gathered by these modern missions rapidly add up to data volume that can no longer be handled with standard work stations and software solutions.Hence,this contribution introduces the TimeScan concept which combines pre-existing tools to an exemplary modular pipeline for the flexible and scalable processing of massive image data collections on a variety of(private or public)computing clusters.The TimeScan framework covers solutions for data access to arbitrary mission archives(with different data provisioning policies)and data ingestion into a processing environment(EO2Data module),mission specific pre-processing of multi-temporal data collections(Data2TimeS module),and the generation of a final TimeScan baseline product(TimeS2Stats module)providing a spectrally and temporally harmonized representation of the observed surfaces.Technically,a TimeScan layer aggregates the information content of hundreds or thousands of single images available for the area and time period of interest(i.e.up to hundreds of TBs or even PBs of data)into a higher level product with significantly reduced volume.In first test,the TimeScan pipeline has been used to process a global coverage of 452,799 multispectral Landsat–8 scenes acquired from 2013 to 2015,a global data-set of 25,550 Envisat ASAR radar images collected 2010–2012,and regional Sentinel–1 and Sentinel–2 collections of∼1500 images acquired from 2014 to 2016.The resulting TimeScan products have already been successfully used in various studies related to the large-scale monitoring of environmental processes and their temporal dynamics.

The ultimate goal of modeling—Simulation of system and plant performance

Modern production processes in chemical, pharmaceutical and biological industries are characterized by complex process structures, which consist of different apparatuses and process steps. Modeling the entire process requires simulating all units altogether, while taking into account interconnections between them, Nevertheless, in the area of solids processing, there is nowadays an unfilled gap from the side of computer support of process modeling in allowing effective optimization and prediction of the behavior of the whole plant, This paper presents a tool for flowsheet simulation which allows the simulation of the stationary behavior of complex processes dealing with solids and its extension towards dynamic modeling, Also, a new simulation concept is proposed on the basis of the multiscale approach. On the macroscale, fiowsheet simulation is performed with the help of the SolidSim system. Parameters for the macromodels in Solid-Sim are predicted by microscale simulation. The models for the two scales are then coupled by inter-scale communication laws. Application of the proposed modeling concept is shown by an example of fluidized bed granulation.

What is going on in magnesium alloys？

China has been developed into one of the most active regions in terms of both fundamental and applied research on magnesium （Mg） and its alloys in the world from a solid base laid by its prominent metallurgist and materials scientists over the past decades. Nowadays, a large number of young-generation researchers have been inspired by their predecessors and become the key participants in the fields of Mg alloys, which consequently led to the establishment of China Youth Scholar Society for Magnesium Alloys Research in 2015. Since then, the first two China Youth Scholars Symposiums on Mg Alloys Research had been held at Harbin （2015） and Chongqing （2016） China, respectively. A number of crucial research inter- ests related to fundamental and applied Mg research were discussed at the conferences and summarized in this short perspective, aiming to boost far-reaching initiatives for development of new Mg-based materials to satisfy the requirements for a broad range of industrial employments. Herein, four main aspects are included as follows： i） Plastic deformation mechanism and strengthening strategy, ii） Design and development of new Mg-based materials, iii） Key service properties, and iv） New processing technologies.

Characterization and Electrochemical Properties of Nanostructured Zr-Doped Anatase TiO_2 Tubes Synthesized by Sol–Gel Template Route

A series of nanostructured Zr-doped anatase TiO_2 tubes with the Zr/Ti molar ratio of 0.01, 0.02, 0.03, and0.09 were prepared by a sol–gel technology on a carbon fiber template. The electrochemical performance of Zr-doped anatase TiO_2 as anodes for rechargeable lithium batteries was investigated and compared with undoped titania. Tests represented that after 35-fold charge/discharge cycling at C/10 the reversible capacity of Zr-doped titania（Zr/Ti = 0.03） reaches 135 m A h g^（-1）, while the capacity of undoped titania（Zr/Ti = 0） yielded only 50 m A h g^（-1）. Based on the results of the physicochemical investigation, three reasons of improving electrochemical performance of Zr-doped titania were suggested. According to the scanning electron microscopy and transmission electron microscopy, Zr^（4＋） doping induces a decrease in nanoparticle size, which facilitates the Li＋diffusion. The Raman investigations show the more open structure of Zr-doped TiO_2 as compared to undoped titania due to changing of the unit cell parameters, that significantly affects on the reversibility of the insertion/extraction process. The electrochemical impedance spectroscopy results indicate that substitution of Zr^（4＋） for Ti^（4＋） into anatase TiO_2 has favorable effects on the conductivity.