Microfluidic field strategy for enhancement and scale up of liquid-liquid homogeneous chemical processes by optimization of 3D spiral baffle structure

Due to the scale effect, the uniform distribution of reagents in continuous flow reactor becomes bad when the channel is enlarged to tens of millimeters. Microfluidic field strategy was proposed to produce high mixing efficiency in large-scale channel. A 3D spiral baffle structure(3SBS) was designed and optimized to form microfluidic field disturbed by continuous secondary flow in millimeter scale Y-shaped tube mixer(YSTM). Enhancement effect of the 3SBS in liquid-liquid homogeneous chemical processes was verified and evaluated through the combination of simulation and experiment. Compared with 1 mm YSTM, 10 mm YSTM with 3SBS increased the treatment capacity by 100 times, shortened the basic complete mixing time by 0.85 times, which proves the potential of microfluidic field strategy in enhancement and scale-up of liquid-liquid homogeneous chemical process.

Scale up and stability test for oxidative coupling of methane over Na_2WO_4-Mn/SiO_2 catalyst in a 200 ml fixed-bed reactor

The study of scale up for the oxidative coupling of methane （OCM） has been carried out in a 200 ml stainless steel fixed-bed reactor over a 5wt% Na2WO4-1.9wt% Mn/SiO2 （W-Mn/SiO2） catalyst. The effects of reaction conditions were investigated in detail. The results showed that, with increasing reaction temperature, the gas-phase reaction was enhanced and a significant amount of methane was converted into COx; with the CH4/O2 molar ratio of 5, the highest C2 （ethylene and ethane） yield of 25% was achieved; the presence of steam （as diluent） had a positive effect on the C2 selectivity and yield. Under lower methane gaseous hourly space velocity （GHSV）, higher selectivity and yield of C2 were obtained as the result of the decrease of released heat energy. In 100 h reaction time, the C2 selectivity of 66%-61% and C2 yield of 24.2%-25.4% were achieved by a single pass without any significant loss in catalytic performance.

Scale Up the Rewards Program in a Steady Way Excerpts from Speech by Zhang Weiqing,Minister of NPFPC

Why scaling up the rewards program for rural families that practice family planning? Rewarding a select number of rural families that practice family planning is a major step that the government takes to improve the country’s family planning program, stabilize the low fertility level, and promote rural socioeconomic development. It is

Upsilon Constants and Their Usefulness in Planck Scale Quantum Cosmology

This paper introduces the two Upsilon constants to the reader. Their usefulness is described with respect to acting as coupling constants between the CMB temperature and the Hubble constant. In addition, this paper summarizes the current state of quantum cosmology with respect to the Flat Space Cosmology (FSC) model. Although the FSC quantum cosmology formulae were published in 2018, they are only rearrangements and substitutions of the other assumptions into the original FSC Hubble temperature formula. In a real sense, this temperature formula was the first quantum cosmology formula developed since Hawking’s black hole temperature formula. A recent development in the last month proves that the FSC Hubble temperature formula can be derived from the Stephan-Boltzmann law. Thus, this Hubble temperature formula effectively unites some quantum developments with the general relativity model inherent in FSC. More progress towards unification in the near-future is expected.

A SUPERLINEARLY CONVERGENT SPLITTING FEASIBLE SEQUENTIAL QUADRATIC OPTIMIZATION METHOD FOR TWO-BLOCK LARGE-SCALE SMOOTH OPTIMIZATION

This paper discusses the two-block large-scale nonconvex optimization problem with general linear constraints.Based on the ideas of splitting and sequential quadratic optimization(SQO),a new feasible descent method for the discussed problem is proposed.First,we consider the problem of quadratic optimal(QO)approximation associated with the current feasible iteration point,and we split the QO into two small-scale QOs which can be solved in parallel.Second,a feasible descent direction for the problem is obtained and a new SQO-type method is proposed,namely,splitting feasible SQO(SF-SQO)method.Moreover,under suitable conditions,we analyse the global convergence,strong convergence and rate of superlinear convergence of the SF-SQO method.Finally,preliminary numerical experiments regarding the economic dispatch of a power system are carried out,and these show that the SF-SQO method is promising.

Functional magnetic resonance imaging study of group independent components underpinning item responses to paranoid-depressive scale

BACKGROUND Our study expand upon a large body of evidence in the field of neuropsychiatric imaging with cognitive,affective and behavioral tasks,adapted for the functional magnetic resonance imaging(MRI)(fMRI)experimental environment.There is sufficient evidence that common networks underpin activations in task-based fMRI across different mental disorders.AIM To investigate whether there exist specific neural circuits which underpin differ-ential item responses to depressive,paranoid and neutral items(DN)in patients respectively with schizophrenia(SCZ)and major depressive disorder(MDD).METHODS 60 patients were recruited with SCZ and MDD.All patients have been scanned on 3T magnetic resonance tomography platform with functional MRI paradigm,comprised of block design,including blocks with items from diagnostic paranoid(DP),depression specific(DS)and DN from general interest scale.We performed a two-sample t-test between the two groups-SCZ patients and depressive patients.Our purpose was to observe different brain networks which were activated during a specific condition of the task,respectively DS,DP,DN.RESULTS Several significant results are demonstrated in the comparison between SCZ and depressive groups while performing this task.We identified one component that is task-related and independent of condition(shared between all three conditions),composed by regions within the temporal(right superior and middle temporal gyri),frontal(left middle and inferior frontal gyri)and limbic/salience system(right anterior insula).Another com-ponent is related to both diagnostic specific conditions(DS and DP)e.g.It is shared between DEP and SCZ,and includes frontal motor/language and parietal areas.One specific component is modulated preferentially by to the DP condition,and is related mainly to prefrontal regions,whereas other two components are significantly modulated with the DS condition and include clusters within the default mode network such as posterior cingulate and precuneus,several occipital areas,including lingual and fusiform gyrus,as well as parahippocampal gyrus.Finally,component 12 appeared to be unique for the neutral condition.In addition,there have been determined circuits across components,which are either common,or distinct in the preferential processing of the sub-scales of the task.CONCLUSION This study has delivers further evidence in support of the model of trans-disciplinary cross-validation in psychiatry.

The laparoscopic rating scale for the evaluation of working conditions for surgical treatment of super-obesity

In this technical note,a novel rating scale(abdominal integral index)was introduced for assessing the conditions of the working laparoscopic space based on linear measurements to select the optimal one or two-stage surgical treatment for super-obesity.Patients with the same height and similar BMI values had different rating scale scores,reflecting different conditions of laparoscopic bariatric surgery.The rating scale helps surgeons and patients make a safe option for surgery,depending on the experience of the surgeon and technical laparoscopic conditions.

On the Fine Structure and the Other Coupling Constants at the Planck Scale

It is shown that the fine structure constant at Planck times tends to one as well as those of the weak and strong interactions. This results by constraining them at the Planck force. That seems to provide interesting new results which confirm that at the beginning of space time (Planck scale) all fundamental forces converge to the same unit value.

Rate-limiting factors in hydrate decomposition through depressurization across various scales:A mini-review

Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the challenges of long-term preparation,high costs and associated risks.Experimental studies,on the other hand,offer a safe and cost-effective means of exploring the mechanisms of hydrate dissociation and optimizing exploitation conditions.Gas hydrate decomposition is a complicated process along with intrinsic kinetics,mass transfer and heat transfer,which are the influencing factors for hydrate decomposition rate.The identification of the rate-limiting factor for hydrate dissociation during depressurization varies with the scale of the reservoir,making it challenging to extrapolate findings from laboratory experiments to the actual exploitation.This review aims to summarize current knowledge of investigations on hydrate decomposition on the subject of the research scale(core scale,middle scale,large scale and field tests)and to analyze determining factors for decomposition rate,considering the various research scales and their associated influencing factors.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Scale effect removal and range migration correction for hypersonic target coherent detection

The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar condition.However,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual application.Thus,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration performance.To eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation angle.Compared to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation capabilities.At last,this paper gives several simulations to assess the viability of ScLRT.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Water as a Standard Substance of a Logarithmic Poison Scale

The lethal dose LD50 represents the most important experimental value for acute toxicity. The simple logarithmic calculation of -log10 LD50 = value leads to the possible poison power pLD. As with the pH or pK value, respectively, for acid or the scale of earthquake intensities the logarithm helps making large differences of orders of magnitude easier to understand since they are more comparable. The higher the pLD value, the higher is the power of poison. An increase of the pLD value by 1 stands for a tenfold increase in toxicity. The lethal acute dose for water, one of the most important and at the same time non-toxic substances of all, is about one tenth of the body weight. This leads to a possible pLD value for water of 1, an ideal starting value for a logarithmic poison scale.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Gravitation, Density Upper Limit and Quantization of Space

The singularity at distance r → 0 at the center of a spherically symmetric non-rotating, uncharged mass of radius R, is considered here. Under inverse square law force, the Schwarzschild metric, needs to be modified, to include Newton’s Shell Theorem (NST). By including NST for r, both Schwarzschild singularity at r = 2GM/c2 and at r → 0 singularities are removed from the metric. Near R → 0, the question of maximal density is considered based on Schwarzschild’s modified metric, and compared to the quantum limit of maximal mass density put by Planck’s quantum-based universal units. It is asserted, that General relativity, when combined with Planck’s universal units, inevitably leads to quantization of gravity.

Evidence for the Reliability and Validity of the Arabic Version of the Student Risk Screening Scale for Internalizing and Externalizing Behaviors (SRSS-IE)

School-based universal screening for behavioral/emotional risk is a necessary first step to providing services in an educational setting for students with emotional and behavioral disorders (EBDs). Psychometric properties are critical to making decisions about choosing a screening instrument. The purpose of the present study was to examine the psychometric properties of the student risk screening scale for internalizing and externalizing behaviors (SRSS-IE). Participants included 3145 students and their teachers. Item-level analyses of the current sample supported the retention of all items. The internal consistency of the SRSS items ranged from 0.83 to 0.85. Convergent validity between the SRSS-IE and a well-established screening tool, the strength and difficulties questionnaire (SDQ), was found for the total score (r = 0.70). Additionally, the results of this study demonstrate strong social validity, suggesting the SRSS-IE to be a useful and functional screening tool. We conclude that the SRSS-IE is a valid and reliable instrument for assessing the level of emotional and behavioral difficulties among elementary students.

High Dimension Multivariate Data Analysis for Small Group Samples of Chemical Volatile Profiles of African Nightshade Species

Quantitative headspace analysis of volatiles emitted by plants or any other living organisms in chemical ecology studies generates large multidimensional data that require extensive mining and refining to extract useful information. More often the number of variables and the quantified volatile compounds exceed the number of observations or samples and hence many traditional statistical analysis methods become inefficient. Here, we employed machine learning algorithm, random forest (RF) in combination with distance-based procedure, similarity percentage (SIMPER) as preprocessing steps to reduce the data dimensionality in the chemical profiles of volatiles from three African nightshade plant species before subjecting the data to non-metric multidimensional scaling (NMDS). In addition, non-parametric methods namely permutational multivariate analysis of variance (PERMANOVA) and analysis of similarities (ANOSIM) were applied to test hypothesis of differences among the African nightshade species based on the volatiles profiles and ascertain the patterns revealed by NMDS plots. Our results revealed that there were significant differences among the African nightshade species when the data’s dimension was reduced using RF variable importance and SIMPER, as also supported by NMDS plots that showed S. scabrum being separated from S. villosum and S. sarrachoides based on the reduced data variables. The novelty of our work is on the merits of using data reduction techniques to successfully reveal differences in groups which could have otherwise not been the case if the analysis were performed on the entire original data matrix characterized by small samples. The R code used in the analysis has been shared herein for interested researchers to customise it for their own data of similar nature.

Evaluation of Digits-in-Noise Test and Hearing Handicap Inventory for Adults Screening in Patients with Occupational Noise-Induced Hearing Loss

Objective:To explore the clinical evaluation role of the Digits-in-Noise(DIN)test and Hearing Handicap Inventory for Adults Screening(HHIA-S)for patients with occupational noise-induced hearing loss and to observe and analyze their application values.Methods:Fifty patients with suspected occupational noise-induced hearing loss were randomly selected from the Department of Otolaryngology at the hospital as the research target.The collection period for the research cases spanned from January 2022 to November 2023,and all patients had a history of noise exposure.The DIN test and HHIA-S were used for hearing examinations,with clinical,comprehensive diagnosis serving as the gold standard to study their diagnostic performance.Results:The compliance rate of the DIN test was 88.00%,the HHIA-S’s compliance rate was 80.00%,and the combined compliance rate was 94.00%.The compliance rate of the DIN test and the combined compliance rates of the patients were statistically significant compared to the clinical gold standard data(P<0.05),while there was no difference between the compliance rate of the HHIA-S and the gold standard(P>0.05).The data shows that the sensitivity of the combined diagnosis is significantly higher than the sensitivity data of the DIN test and HHIA-S examination alone(P<0.05).Its specificity is 100.00%,and the accuracy data of the joint diagnosis in the degree were higher than those of the DIN test alone(P>0.05)and the HHIA-S alone(P<0.05).Conclusion:For patients with occupational noise-induced hearing loss,the joint evaluation of the DIN test and HHIA-S can significantly improve their diagnostic value with high sensitivity and accuracy.

Scale-up of biomass conversion using 1-ethyl-3-methylimidazolium acetate as the solvent

This scale-up study demonstrated the feasibility of an ionic liquid(IL)pretreatment process at 40 kg scale,using the IL 1-ethyl-3-methylimidazolium acetate([C2C1Im][OAc])as the solvent.The pretreatment was followed by enzymatic hydrolysis through which the process efficiency for biomass conversion to monomeric sugars was determined.The results show that 43 wt%of switchgrass was dissolved in IL after 2 h of pretreatment at 160℃ with 15 wt%solid loading.A 120 h enzymatic hydrolysis of the pretreated switchgrass results in 96%glucan and 98%xylan conversion.[C2C1Im][OAc]pretreatment has been successfully scaled up to 40 kg with improved sugar titers and yields relative to bench scale(6 kg).The mass flow of the overall process was established and the major scale-up challenges of the process were identified.