Adjustment of Administrative Divisions and Upgrading of Industrial Structure in Hefei Metropolitan Area:Taking"Partitions of Chaohu"as a Quasi-natural Experiment

Administrative regions are an important environment for the operation of China's market economy.The relevant economic subjects cannot predict the policy of adjustment of administrative divisions and carry out conscious migration behavior,adjustment of administrative divisions can be regarded as a quasi-natural experiment.The three cities of Hefei,Wuhu,and Ma'anshan,which are directly related to the adjustment of the administrative division of Chaohu,are taken as the treatment group,and the seven adjacent cities of Lu'an,Huainan,Chuzhou,Bengbu,Anqing,Chizhou,and Tongling are taken as the control group.Differences-in-Differences method and relevant control variables affecting the upgrading of industrial structure are used to test.The test results show that"Partitions of Chaohu"has a significant industrial structure upgrading effect by promoting the optimization of spatial layout,the cross-regional flow of production factors and the effective management of Chaohu Lake Basin.At the same time,the increase of total retail sales of consumer goods,urban fixed assets investment,public utility expenses in science,education,culture and health,and population plays a significant positive role in promoting the upgrading of industrial structure,while foreign direct investment plays a certain inhibition role in the upgrading of industrial structure.In order to meet the ever-developing space demands and enhance the impact on surrounding areas,the Hefei metropolitan area should be driven by technological innovation,strengthen the integration of industrial chains,improve the business environment and transportation network,and continuously promote the upgrading of industrial structure and the formation and development of new productive forces.

Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

Potential industrial applications of photo/electrocatalysis: Recent progress and future challenges

Nowadays,the rapid development of the social economy inevitably leads to global energy and environmental crisis.For this reason,more and more scholars focus on the development of photocatalysis and/or electrocatalysis technology for the advantage in the sustainable production of high-value-added products,and the high efficiency in pollutants remediation.Although there is plenty of outstanding research has been put forward continuously,most of them focuses on catalysis performance and reaction mechanisms in laboratory conditions.Realizing industrial application of photo/electrocatalytic processes is still a challenge that needs to be overcome by social demand.In this regard,this review comprehensively summarized several explorations in thefield of photo/electrocatalytic reduction towards potential industrial applications in recent years.Special attention is paid to the successful attempts and the current status of photo/electrocatalytic water splitting,carbon dioxide conversion,resource utilization from waste,etc.,by using advanced reactors.The key problems and challenges of photo/electrocatalysis in future industrial practice are also discussed,and the possible development directions are also pointed out from the industry view.

Predicting the probability distribution of Martian rocks mechanical property based on microscale rock mechanical experiments and accurate grain-based modeling

The exploration of Mars would heavily rely on Martian rocks mechanics and engineering technology.As the mechanical property of Martian rocks is uncertain,it is of utmost importance to predict the probability distribution of Martian rocks mechanical property for the success of Mars exploration.In this paper,a fast and accurate probability distribution method for predicting the macroscale elastic modulus of Martian rocks was proposed by integrating the microscale rock mechanical experiments(micro-RME),accurate grain-based modeling(AGBM)and upscaling methods based on reliability principles.Firstly,the microstructure of NWA12564 Martian sample and elastic modulus of each mineral were obtained by micro-RME with TESCAN integrated mineral analyzer(TIMA)and nanoindentation.The best probability distribution function of the minerals was determined by Kolmogorov-Smirnov(K-S)test.Secondly,based on best distribution function of each mineral,the Monte Carlo simulations(MCS)and upscaling methods were implemented to obtain the probability distribution of upscaled elastic modulus.Thirdly,the correlation between the upscaled elastic modulus and macroscale elastic modulus obtained by AGBM was established.The accurate probability distribution of the macroscale elastic modulus was obtained by this correlation relationship.The proposed method can predict the probability distribution of Martian rocks mechanical property with any size and shape samples.

Network pharmacology study and in vitro experimental validation of Xiaojianzhong decoction against gastric cancer

BACKGROUND Cancer is one of the most serious threats to human health worldwide.Conventional treatments such as surgery and chemotherapy are associated with some drawbacks.In recent years,traditional Chinese medicine treatment has been increasingly advocated by patients and attracted attention from clinicians,and has become an indispensable part of the comprehensive treatment for gastric cancer.AIM To investigate the mechanism of Xiaojianzhong decoction(XJZ)in the treatment of gastric cancer(GC)by utilizing network pharmacology and experimental validation,so as to provide a theoretical basis for later experimental research.METHODS We analyzed the mechanism and targets of XJZ in the treatment of GC through network pharmacology and bioinformatics.Subsequently,we verified the impact of XJZ treatment on the proliferative ability of GC cells through CCK-8,apoptosis,cell cycle,and clone formation assays.Additionally,we performed Western blot analysis and real-time quantitative PCR to assess the protein and mRNA expression of the core proteins.RESULTS XJZ mainly regulates IL6,PTGS2,CCL2,MMP9,MMP2,HMOX1,and other target genes and pathways in cancer to treat GC.The inhibition of cell viability,the increase of apoptosis,the blockage of the cell cycle at the G0/G1 phase,and the inhibition of the ability of cell clone formation were observed in AGS and HGC-27 cells after XJZ treatment.In addition,XJZ induced a decrease in the mRNA expression of IL6,PTGS2,MMP9,MMP2,and CCL2,and an increase in the mRNA expression of HOMX1.XJZ significantly inhibited the expression of IL6,PTGS2,MMP9,MMP2,and CCL2 proteins and promoted the expression of the heme oxygenase-1 protein.CONCLUSION XJZ exerts therapeutic effects against GC through multiple components,multiple targets,and multiple pathways.Our findings provide a new idea and scientific basis for further research on the molecular mechanisms underlying the therapeutic effects of XJZ in the treatment of GC.

Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet.Traditional signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging attacks.Therefore,there is the need for an IDS which can learn from data and detect new threats.Ensemble Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking technique.In this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta learner.The proposed DSNN model was trained and evaluated with the next-generation dataset,TON_IoT.Several pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE technique.Accuracy,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble model.Our experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML models.In addition,the model proposed for IDS has been compared with similar models.The proposed DSNN achieved better performance metrics than the other models.The proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

Impact of an official accountability audit on industrial structure adjustment:a case study of environmental regulation in China

As a unique environmental regulation in China,the official accountability audit was piloted in 2014.With a focus on prioritizing the ecological environment,officials in pilot districts have implemented economic construction,adjusted industrial structures,and promoted coordinated development between the economy and environment.The effects of implementation have garnered widespread attention from society.However,there is limited research on the impact of an accountability audit on industrial structure adjustments.Using the“Accountability Audit of Officials for Natural Resource Assets(Trial)”released in 2015 as a quasi-natural experiment,this study collected panel data from 279 cities between 2013 and 2017.It then empirically analyzed the impact mechanism and effects of the accountability audit on industrial structure adjustment using the Propensity Score Matching and Difference-in-Differences model.The research findings indicate that the accountability audit directly impacted industrial structure adjustment,promoting the upgrading of the primary industry to the secondary industry and restricting the development of the tertiary industry.In addition,the audit is beneficial for enterprise entry,but not conducive to technological innovation,and has no significant impact on foreign direct investment.This conclusion fills a gap in the existing research and provides valuable insights for policymakers.

Can Industrial Structure Upgrading Restrain Industrial Land Expansion?Evidence from China

China has made great achievements in industrial development and is transforming into a powerful manufacturing country.Meanwhile,the industrial land scale is also expanding.However,whether industrial structure upgrading achieves the purpose of restraining industrial land expansion remains unanswered.By calculating the industrial land structure index(ILSI)and industrial land expansion scale(ILES),this study analyzed their temporal and spatial distribution characteristics at both regional and city levels from 2007to 2020 in China.Results show that industrial land expansion presents a different trend in the four regions,the ILES in the eastern region is the largest,and the speed of industrial land expansion has declined since 2013,but it has gradually increased since 2016.The ILSI of the eastern and central regions is higher than that of the western and northeastern regions.Furthermore,a spatial Durbin model(SDM)has been established to estimate the spatial effect of industrial structure upgrading on industrial land expansion from 2007 to2020.Notably,industrial structure upgrading has not slowed industrial land expansion.The eastern and western regions require a greater amount of industrial land while upgrading the industrial structure.The improvement of the infrastructure level and international trade level has promoted industrial land expansion.

Design and analysis of an advanced thermal management system for the solar close observations and proximity experiments spacecraft

In this paper,the mission and the thermal environment of the Solar Close Observations and Proximity Experiments(SCOPE)spacecraft are analyzed,and an advanced thermal management system(ATMS)is designed for it.The relationship and functions of the integrated database,the intelligent thermal control system and the efficient liquid cooling system in the ATMS are elaborated upon.For the complex thermal field regulation system and extreme space thermal environment,a modular simulation and thermal field planning method are proposed,and the feasibility of the planning algorithm is verified by numerical simulation.A solar array liquid cooling system is developed,and the system simulation results indicate that the temperatures of the solar arrays meet the requirements as the spacecraft flies by perihelion and aphelion.The advanced thermal management study supports the development of the SCOPE program and provides a reference for the thermal management in other deep-space exploration programs.

Spatial Patterns and Drivers of Intelligent Manufacturing from a‘Glob-allocal'Perspective:A Study of China's Industrial Robotics

The advancement of the intelligent manufacturing industry(IMI)represents the future direction for the world's manufactur-ing sector,offering a promising avenue to bolster national competitiveness and enhance industrial manufacturing efficiency.In this study,we took the industrial robot industry(IRI)as a case study to elucidate the spatial distribution and interconnections of IMI from a geographical perspective,and the modified diamond model(DM)was used to analyze the influencing factors.Results show that:1)the spatial pattern of IRI with various investment attributes in different industrial chain links is generally similar,centered in the southeast.Key investment areas are in the east and south.The spatial distribution of China's IRI covers a multitude of provinces and obtains differ-ent scales of investment in different countries(regions).2)The spatial correlation between foreign investors and China's provincial-level administrative regions(PARs)forms a network,and the network of foreign-invested enterprises is more stable.Different countries(regions)have distinct location preferences in China,with significant spatial differences in correlation degrees.3)Overall,the interac-tion of these factors shapes the location decisions and correlation patterns of industrial robot enterprises.This study not only contributes to our theoretical knowledge of the industrial spatial structure and industrial economy but also offers valuable references and sugges-tions for national IMI planning and relevant industry investors.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Mechanical heterogeneity characterization of coal materials based on nano-indentation experiments

To investigate the complex macro-mechanical properties of coal from a micro-mechanical perspective,we have conducted a series of micro-mechanical experiments on coal using a nano-indentation instrument.These experiments were conducted under both dynamic and static loading conditions,allowing us to gather the micro-mechanical parameters of coal for further analysis of its micro-mechanical heterogeneity using the box counting statistical method and the Weibull model.The research findings indicate that the load–displacement curves of the coal mass under the two different loading modes exhibit noticeable discreteness.This can be attributed to the stress concentration phenomenon caused by variations in the mechanical properties of the micro-units during the loading process of the coal mass.Consequently,there are significant fluctuations in the micro-mechanical parameters of the coal mass.Moreover,the mechanical heterogeneity of the coal at the nanoscale was confirmed based on the calculation results of the standard deviation coefficient and Weibull modulus of the coal body’s micromechanical parameters.These results reveal the influence of microstructural defects and minerals on the uniformity of the stress field distribution within the loaded coal body,as well as on the ductility characteristics of the micro-defect structure.Furthermore,there is a pronounced heterogeneity in the micromechanical parameters.Furthermore,we have established a relationship between the macro and micro elastic modulus of coal by applying the Mori-Tanaka homogenization method.This relationship holds great significance for revealing the micro-mechanical failure mechanism of coal.

Technological anxiety:Analysis of the impact of industrial intelligence on employment in China

Employment is the greatest livelihood.Whether the impact of industrial robotics technology materialized in machines on employment in the digital age is an“icing on the cake”or“adding fuel to the fire”needs further study.This study aims to analyze the impact of the installation and application of industrial robots on labor demand in the context of the Chinese economy.First,from the theoretical logic and the economic development law,this study gives the prior judgment and research hypothesis that industrial intelligence will increase jobs.Then,based on the panel data of 269 cities in China from 2006 to 2021,we use the two-way fixed effect model,dynamic threshold model,and two-stage intermediary effect model.The objective is to investigate the impact of industrial intelligence on enterprise labor demand and its path mechanism.Results show that the overall effect of industrial intelligence on the labor force with the installation density index of industrial robots as the proxy variable is the“creation effect”.In other words,advanced digital technology has created additional jobs,and the overall supply of employment in the labor market has increased.The conclusion is still valid after the endogeneity identification and robustness test.In addition,the positive effect has a nonlinear effect on the network scale.When the installation density of industrial robots exceeds a particular threshold value,the division of labor continues to deepen under the combined action of the production efficiency and compensation effects,which will cause enterprises to increase labor demand further.Further research showed that industrial intelligence can increase employment by promoting synergistic agglomeration and improving labor price distortions.This study concludes that in the digital China era,the introduction and installation of industrial robots by enterprises can affect the optimal allocation of the labor market.This phenomenon has essential experience and reference significance for guiding industrial digitalization and intelligent transformation and promoting the high-quality development of people’s livelihood.

China’s Industrial Modernization:Development Rationale,Current Status,and Policy Directions

Economies that have effectively escaped the“middle-income trap”demonstrate common traits in their industrial restructuring as they progressed to high-income status.These include a relatively stable share of an economy’s manufacturing sector,a reasonable economic structure,enhanced industrial capabilities,and growth driven by innovation.However,late-moving countries face a number of hurdles as they strive to cross this threshold.China’s development advantages include,among other things,a complete industrial system,a more balanced industrial structure,growing indigenous innovation capabilities,continual expansion and upgrading of domestic demand,and a greater degree of openness.These capabilities have provided continuous momentum for industrial growth,allowing China to capitalize on the next wave of technological and industrial revolutions while also promoting long-term,steady industrial development.During its modernization efforts,China has seen substantial changes in the external environment surrounding its industrial development.We must not only recognize the increasing complexity,intensity,and uncertainty of these changes,but also take proactive steps to solve diverse issues and capitalize on opportunities arising from global digital and green transitions.Equal focus should be placed on strengthening reforms and promoting high-level openness,improving policy coordination and consistency,and pursuing an innovation-driven strategy.This will speed the development of a modern industrial system and encourage the formation of new,high-quality productive forces.

Experimental Investigation on Vertical Hydraulic Transport of Ores in Deepsea Mining

Deepsea mining has been proposed since the 1960s to alleviate the lack of resources on land.Vertical hydraulic transport of collected ores from the seabed to the sea surface is considered the most promising method for industrial applications.In the present study,an indoor model test of the vertical hydraulic transport of particles was conducted.A noncontact optical method has been proposed to measure the local characteristics of the particles inside a vertical pipe,including the local concentration and particle velocity.The hydraulic gradient of ore transport was evaluated with various particle size distributions,particle densities,feeding concentrations and mixture flow velocities.During transport,the local concentration is larger than the feeding concentration,whereas the particle velocity is less than the mixture velocity.The qualitative effects of the local concentration and local fluid velocity on the particle velocity and slip velocity were investigated.The local fluid velocity contributes significantly to particle velocity and slip velocity,whereas the effect of the local concentration is marginal.A higher feeding concentration and mixture flow velocity result in an increased hydraulic gradient.The effect of the particle size gradation is slight,whereas the particle density plays a crucial role in the transport.

From the perspective of experimental practice: High-throughput computational screening in photocatalysis

Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.

DTAIS:Distributed trusted active identity resolution systems for the Industrial Internet

In recent years,the Industrial Internet and Industry 4.0 came into being.With the development of modern industrial intelligent manufacturing technology,digital twins,Web3 and many other digital entity applications are also proposed.These applications apply architectures such as distributed learning,resource sharing,and arithmetic trading,which make high demands on identity authentication,asset authentication,resource addressing,and service location.Therefore,an efficient,secure,and trustworthy Industrial Internet identity resolution system is needed.However,most of the traditional identity resolution systems follow DNS architecture or tree structure,which has the risk of a single point of failure and DDoS attack.And they cannot guarantee the security and privacy of digital identity,personal assets,and device information.So we consider a decentralized approach for identity management,identity authentication,and asset verification.In this paper,we propose a distributed trusted active identity resolution system based on the inter-planetary file system(IPFS)and non-fungible token(NFT),which can provide distributed identity resolution services.And we have designed the system architecture,identity service process,load balancing strategy and smart contract service.In addition,we use Jmeter to verify the performance of the system,and the results show that the system has good high concurrent performance and robustness.

Experimental and numerical study of buckling-restrained braces configured with out-of-plane eccentricity under cyclic loading

This study focuses on variations in the hysteretic behavior of buckling-restrained braces(BRBs)configured with or without out-of-plane eccentricity under cyclic loading.Quasi-static experiments and numerical simulations were carried out on concentrically and eccentrically loaded BRB specimens to investigate the mechanical properties,energy dissipation performance,stress distribution,and high-order deformation pattern.The experimental and numerical results showed that compared to the concentrically loaded BRBs,the stiffness,yield force,cumulated plastic ductility(CPD)coefficient,equivalent viscous damping coefficient and energy dissipation decreased,and the yield displacement and compression strength adjustment factor increased for the eccentrically loaded BRBs.With the existence of the out-of-plane eccentricity,the initial yield position changes from the yield segment to the junction between the yield segment and transition segment under a tensile load,while the initial high-order buckling pattern changes from a first-order C-shape to a secondorder S-shape under a compressive load.

Influence of axial stress on rockburst in deep tunnels: insight from model experiment

Frequent rockburst disasters in deep-buried engineering projects severely impact construction. To explore the influence of axial stress on rockburst in deep-buried tunnels, large-scale true triaxial rockburst experiments were conducted under four different axial stress ratio conditions (ηt, axial loading stress/vertical loading stress) using a self-developed true triaxial loading device under the condition of "pre-loading before excavation". The influence of axial stress on the rockburst process and failure characteristics in deep tunnels was studied using a combination of real-time video monitoring, rockburst debris sieving, and acoustic emission monitoring. The results indicate: (1) all four specimens subjected to different axial stress ratio loading conditions exhibited three stages of macroscopic failure: small particle ejection, flake spalling, and large fragment ejection. Ultimately, "V"-shaped notches appeared on both sides of the tunnel. (2) The failure stress, fragment volume, and fragment size distribution of the rockburst specimens exhibited a clear two-stage failure characteristic with increasing axial stress ratio. In the lower axial stress ratio stage (ηt ≤ 0.7), the increase in the axial stress ratio enhances lateral confinement, thereby increasing the crack initiation strength of the surrounding rock, inhibiting crack formation and propagation, and thus suppressing damage to the surrounding rock of the tunnel. In the higher axial stress ratio stage (ηt > 0.7), the increase in axial stress ratio makes the Poisson effect of the surrounding rock more pronounced, promoting the generation and propagation of cracks along the tunnel axis direction, thereby promoting damage to the surrounding rock. (3) Based on the analysis of acoustic emission parameters (fracture properties), it can be concluded that in the lower axial stress ratio stage (ηt ≤ 0.7), an increase in the axial stress ratio leads to a higher proportion of shear fracture in rockburst damage. Conversely, in the higher axial stress ratio stage (ηt > 0.7), the increase in axial stress ratio gradually reduces the proportion of shear fracture in rockburst damage.

Development and Validation of Integrated Nutrient Management Practices of Industrial Processing Varieties: Asterix and Courage in Bangladesh

An experiment was meticulously conducted at the research field of Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, Bangladesh, during the 2011-2012 potato growing season to develop integrated crop management practices for the potato seed production of industrial processing varieties Asterix and Courage. Significantly, higher growth and yield parameters were found in the BADC-recommended practice. Later, another experiment was conducted to validate the BADC practice during the 2013-2014 potato growing season in two locations in Bangladesh. Results showed that the production of tuber per hill, tuber weight per hill as well as gross tuber yield per plot, higher proportion of storable seed tubers, and more quality seed potatoes (A-grade and B-grade) seed tubers were found significantly higher in the “BADC developed practice” compared to other treatments. Viral diseases (PLRV and PVY) prevalence was lower in “BADC developed practice”. Moreover, “BADC developed practice” contributed more economic yield by minimizing input cost compared to “Munshiganj advanced farmers’ practice”. Therefore, the “BADC developed practice” was found “superior” regarding yield, quality, and profitability in seed potato production of industrial varieties—Asterix and Courage in Bangladesh.