Application of GNSS-PPP on Dynamic Deformation Monitoring of Offshore Platforms

The real-time dynamic deformation monitoring of offshore platforms under environmental excitation is crucial to their safe operation.Although Global Navigation Satellite System-Precise Point Positioning(GNSS-PPP)has been considered for this purpose,its monitoring accuracy is relatively low.Moreover,the influence of background noise on the dynamic monitoring accuracy of GNSS-PPP remains unclear.Hence,it is imperative to further validate the feasibility of GNSS-PPP for deformation monitoring of offshore platforms.To address these concerns,vibration table tests with different amplitudes and frequencies are conducted.The results demonstrate that GNSS-PPP can effectively monitor horizontal vibration displacement as low as±30 mm,which is consistent with GNSS-RTK.Furthermore,the spectral characteristic of background noise in GNSS-PPP is similar to that of GNSS-RTK(Real Time Kinematic).Building on this observation,an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)has been proposed to de-noise the data and enhance the dynamic monitoring accuracy of GNSS-PPP.Field monitoring application research is also undertaken,successfully extracting and analyzing the dynamic deformation of an offshore platform structure under environmental excitation using GNSS-PPP monitoring in conjunction with improved CEEMDAN de-noising.By comparing the de-noised dynamic deformation trajectories of the offshore platform during different periods,it is observed that the platform exhibits reversible alternating vibration responses under environmental excitation,with more pronounced displacement deformation in the direction of load action.The research results confirm the feasibility and potential of GNSS-PPP for dynamic deformation monitoring of offshore platforms.

Enterprise 2支架治疗颅内动脉瘤的临床效果分析

目的 研究分析颅内动脉瘤在临床治疗环节中Enterprise 2支架的应用效果。方法 选取2021年6月—2022年12月在本院接受治疗的60例颅内动脉瘤患者展开试验分析,按照其治疗方式进行分组,将采用Enterprise 2支架展开治疗的患者作为观察组,选择保守治疗的患者30例作为对照组,对比两组患者治疗成功率以及临床症状改善情况。结果 经治疗,观察组患者治疗成功率显著高于对照组(P<0.05);经过6个月的随访发现,观察组患者临床症状改善情况显著优于对照组,差异具有统计学意义(P<0.05);观察组患者满意度显著优于对照组,差异具有统计学意义(P<0.05)。结论 Enterprise 2支架治疗操作比较简单,并且可以取得良好的治疗效果,相较于保守治疗而言,治疗效果显著,可以有效改善患者预后,值得在临床推广应用。

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

Design and Construction of Automatic Monitoring System for Open-pit Coal Mine Slopes

[Objectives]To monitor the stability of open-pit coal mine slopes in real time and ensure the safety of coal mine production.[Methods]The automatic monitoring system of coal mine slope was explored in depth,and the core functions of the system were designed comprehensively.According to the design function of the automatic monitoring system,the slope automatic monitoring system was constructed.Besides,in accordance with the actual situation of the slope,the monitoring frequency of slopes was set scientifically,and the key indicators such as rainfall,deep displacement and surface displacement of the slopes were monitored in an all-round and multi-angle way.[Results]During the monitoring period,the overall condition of the slope remained good,and no landslides or other geological disasters occurred.At the same time,the overall rainfall in the slope area remained low.In terms of monitoring data,the horizontal displacement and settlement of the slopes increased first and then tended to be stable.Specifically,the maximum horizontal displacement during the monitoring period was 22.74 mm,while the maximum settlement was 18.65 mm.[Conclusions]The automatic slope monitoring system has obtained remarkable achievements in practical application.It not only improves the accuracy and efficiency of slope stability monitoring,but also provides valuable reference experience for similar projects.

Accuracy of FreeStyle Libre flash glucose monitoring in patients with type 2 diabetes who migrated from highlands to plains

BACKGROUND The FreeStyle Libre flash glucose monitoring(FGM)system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose.Due to its increased usage in clinics,the number of studies investigating its accuracy has increased.However,its accuracy has not been investigated in highland populations in China.AIM To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes(T2D)who had migrated within 3 mo from highlands to plains.METHODS Overall,68 patients with T2D,selected from those who had recently migrated from highlands to plains(within 3 mo),were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring(CGM)with the FreeStyle Libre FGM system for 14 d.Throughout the study period,fingertip capillary blood glucose was measured daily using the enzyme electrode method(Super GL,China),and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals.Moreover,the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to<5 min.The accuracy of the FGM system was evaluated according to the CGM guidelines.Subsequently,the factors influencing the mean absolute relative difference(MARD)of this system were analyzed by a multiple linear regression method.RESULTS Pearson’s correlation analysis showed that the fingertip and scanned glucose levels were positively correlated(R=0.86,P=0.00).The aggregated MARD of scanned glucose was 14.28±13.40%.Parker's error analysis showed that 99.30%of the data pairs were located in areas A and B.According to the probe wear time of the FreeStyle Libre FGM system,MARD_(1 d) and MARD_(2-14 d) were 16.55%and 14.35%,respectively(t=1.23,P=0.22).Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion(LAGE)was<5.80 mmol/L but negatively correlated with blood glucose when the LAGE was≥5.80 mmol/L.CONCLUSION The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains.This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains.MARD is mainly influenced by glucose levels and fluctuations,and the accuracy of the system is higher when the blood glucose fluctuation is small.In case of higher blood glucose level fluctuations,deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.

Contract Mechanism of Water Environment Regulation for Small and Medium Sized Enterprises Based on Optimal Control Theory

The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.

Application and management of continuous glucose monitoring in diabetic kidney disease

Diabetic kidney disease(DKD)is a common complication of diabetes mellitus that contributes to the risk of end-stage kidney disease(ESKD).Wide glycemic var-iations,such as hypoglycemia and hyperglycemia,are broadly found in diabetic patients with DKD and especially ESKD,as a result of impaired renal metabolism.It is essential to monitor glycemia for effective management of DKD.Hemoglobin A1c(HbA1c)has long been considered as the gold standard for monitoring glycemia for>3 months.However,assessment of HbA1c has some bias as it is susceptible to factors such as anemia and liver or kidney dysfunction.Continuous glucose monitoring(CGM)has provided new insights on glycemic assessment and management.CGM directly measures glucose level in interstitial fluid,reports real-time or retrospective glucose concentration,and provides multiple glycemic metrics.It avoids the pitfalls of HbA1c in some contexts,and may serve as a precise alternative to estimation of mean glucose and glycemic variability.Emerging studies have demonstrated the merits of CGM for precise monitoring,which allows fine-tuning of glycemic management in diabetic patients.Therefore,CGM technology has the potential for better glycemic monitoring in DKD patients.More research is needed to explore its application and management in different stages of DKD,including hemodialysis,peritoneal dialysis and kidney transplantation.

A Fuzzy Trust Management Mechanism with Dynamic Behavior Monitoring for Wireless Sensor Networks

Traditional wireless sensor networks(WSNs)are typically deployed in remote and hostile environments for information collection.The wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various attacks.Traditional encryption and authentication mechanisms cannot prevent attacks launched by internal malicious nodes.The trust-based security mechanism is usually adopted to solve this problem in WSNs.However,the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor nodes.Moreover,how to efficiently collect behavioral evidences are rarely discussed.To address these issues,in this paper,we present a trust management mechanism based on fuzzy logic and a cloud model.First,a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate uncertainty.Then,the cloud model is introduced to estimate the trust values for sensor nodes.Finally,a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety assurance.Simulation results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.

Survey and Prospect for Applying Knowledge Graph in Enterprise Risk Management

Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order.Amidst the challenges posed by intricate and unpredictable risk factors,knowledge graph technology is effectively driving risk management,leveraging its ability to associate and infer knowledge from diverse sources.This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios.Firstly,employing bibliometric methods,the aim is to uncover the developmental trends and current research hotspots within the domain of enterprise risk knowledge graphs.In the succeeding section,systematically delineate the technical methods for knowledge extraction and fusion in the standardized construction process of enterprise risk knowledge graphs.Objectively comparing and summarizing the strengths and weaknesses of each method,we provide recommendations for addressing the existing challenges in the construction process.Subsequently,categorizing the applied research of enterprise risk knowledge graphs based on research hotspots and risk category standards,and furnishing a detailed exposition on the applicability of technical routes and methods.Finally,the future research directions that still need to be explored in enterprise risk knowledge graphs were discussed,and relevant improvement suggestions were proposed.Practitioners and researchers can gain insights into the construction of technical theories and practical guidance of enterprise risk knowledge graphs based on this foundation.

Optimizing Enterprise Conversational AI: Accelerating Response Accuracy with Custom Dataset Fine-Tuning

As the realm of enterprise-level conversational AI continues to evolve, it becomes evident that while generalized Large Language Models (LLMs) like GPT-3.5 bring remarkable capabilities, they also bring forth formidable challenges. These models, honed on vast and diverse datasets, have undoubtedly pushed the boundaries of natural language understanding and generation. However, they often stumble when faced with the intricate demands of nuanced enterprise applications. This research advocates for a strategic paradigm shift, urging enterprises to embrace a fine-tuning approach as a means to optimize conversational AI. While generalized LLMs are linguistic marvels, their inability to cater to the specific needs of businesses across various industries poses a critical challenge. This strategic shift involves empowering enterprises to seamlessly integrate their own datasets into LLMs, a process that extends beyond linguistic enhancement. The core concept of this approach centers on customization, enabling businesses to fine-tune the AI’s functionality to fit precisely within their unique business landscapes. By immersing the LLM in industry-specific documents, customer interaction records, internal reports, and regulatory guidelines, the AI transcends its generic capabilities to become a sophisticated conversational partner aligned with the intricacies of the enterprise’s domain. The transformative potential of this fine-tuning approach cannot be overstated. It enables a transition from a universal AI solution to a highly customizable tool. The AI evolves from being a linguistic powerhouse to a contextually aware, industry-savvy assistant. As a result, it not only responds with linguistic accuracy but also with depth, relevance, and resonance, significantly elevating user experiences and operational efficiency. In the subsequent sections, this paper delves into the intricacies of fine-tuning, exploring the multifaceted challenges and abundant opportunities it presents. It addresses the technical intricacies of data integration, ethical considerations surrounding data usage, and the broader implications for the future of enterprise AI. The journey embarked upon in this research holds the potential to redefine the role of conversational AI in enterprises, ushering in an era where AI becomes a dynamic, deeply relevant, and highly effective tool, empowering businesses to excel in an ever-evolving digital landscape.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB drugs.New strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and recommended.Liquid chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous compounds.This technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics analysis.TDM improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window.Based on TDM,the dose would be optimized individually to achieve favorable outcomes.Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome evaluation.This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades.Besides,we discussed the advantages and disadvantages of this technique in practical use.The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted.Lastly,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

Nanomaterial-assisted wearable glucose biosensors for noninvasive real-time monitoring:Pioneering point-of-care and beyond

This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose detection.In addition,examines key strategies for designing glucose sensors that are multi-functional,reliable,and cost-effective in a variety of contexts.The unique features of effective diabetes management technology are highlighted,with a focus on using nano/biosensor devices that can quickly and accurately detect glucose levels in the blood,improving patient treatment and control of potential diabetes-related infections.The potential of next-generation wearable and touch-sensitive nano biomedical sensor engineering designs for providing full control in assessing implantable,continuous glucose monitoring is also explored.The challenges of standardizing drug or insulin delivery doses,low-cost,real-time detection of increased blood sugar levels in diabetics,and early digital health awareness controls for the adverse effects of injectable medication are identified as unmet needs.Also,the market for biosensors is expected to expand significantly due to the rising need for portable diagnostic equipment and an ever-increasing diabetic population.The paper concludes by emphasizing the need for further research and development of glucose biosensors to meet the stringent requirements for sensitivity and specificity imposed by clinical diagnostics while being cost-effective,stable,and durable.

Clinical/Behavioral Monitoring of Rodents and Rabbits Undergoing Scientific Experiments

Background: We currently have international and national guidelines regarding the assessment and monitoring of clinical signs and humane endpoints in animals used in teaching and research, which make the performance of these activities mandatory for any experiment and professional working in this area. Assigning the severity of a research experiment is the result of an analysis of records of observations of the animal’s behavior, and clinical signs. The aim of this study was to describe the importance of carrying out a severity assessment associated with clinical and behavioral monitoring of rodents and rabbits during experimentation to maintain the welfare of these animals undergoing scientific research. Methods: The literature search was carried out using the following terms: “Monitoring”;“Humane endpoints”;“Animal welfare”, “Rodents”;“Rabbits”, and as connectors “and”;“or”, in the following databases: PubMed;LILACS/BIREME and SciELO. Results: A total of 987 articles were identified in the databases, and 20 of these studies were included in this review. Conclusions: Humane endpoint protocols and procedure severity tables are of the utmost importance, both from an ethical point and to refine the results of research conducted on laboratory animals. They should be drawn up jointly by the teams responsible for the project and the maintenance of the animals during the research period, and the data obtained should be published so that the scientific community can have access to it, helping to disseminate these practices, as well as helping to draw up new procedures. Monitoring and evaluating the welfare and clinical condition of animals undergoing scientific research procedures is the responsibility of the professors, researchers, veterinarians, and animal facility coordinators. The Ethics Committee on the Use of Animals must monitor all the activities conducted with the animals, by inspecting the experimental procedures and the physical environment of the laboratory animal facility where the animals are housed.

An improved typhoon monitoring model based on precipitable water vapor and pressure

The potential of monitoring the movement of typhoons using the precipitable water vapor(PWV) has been confirmed. However, monitoring the movement of typhoon is focused on PWV, making it difficult to describe the movement of a typhoon in detail minutely and resulting in insufficient accuracy. Hence,based on PWV and meteorological data, we propose an improved typhoon monitoring mode. First, the European Centre for Medium-Range Weather Forecasts Reanalysis 5-derived PWV(ERA5-PWV) and the Global Navigation Satellite System-derived PWV(GNSS-PWV) were compared with the reference radiosonde PWV(RS-PWV). Then, using the PWV and atmospheric parameters derived from ERA5, we discussed the anomalous variations of PWV, pressure(P), precipitation, and wind speed during different typhoons. Finally, we compiled a list of critical factors related to typhoon movement, PWV and P. We developed an improved multi-factor typhoon monitoring mode(IMTM) with different models(i.e.,IMTM-I and IMTM-II) in different cases with a higher density of GNSS observation or only Numerical Weather Prediction(NWP) data. The IMTM was evaluated through the reference movement speeds of HATO and Mangkhut from the China Meteorological Observatory Typhoon Network(CMOTN). The results show that the root mean square(RMS) of the IMTM-I is 1.26 km/h based on ERA5-P and ERA5-PWV,and the absolute bias values are mostly within 2 km/h. Compared with the models considering the single factor ERA5-P/ERA5-PWV, the RMS of the IMTM-I is improved by 26.3% and 38.5%, respectively. The IMTM-II model manifests a residual of only 0.35 km/h. Compared with the single-factor model based on GNSS-PWV/P, the residual of the IMTM-II model is reduced by 90.8% and 84.1%, respectively. These results propose that the typhoon movement monitoring approach combining PWV and P has evident advantages over the single-factor model and is expected to supplement traditional typhoon monitoring.

Impact of the carbon market on investment benefits of power-grid enterprises in China: a system dynamics analysis

The power grid,as the hub connecting the power supply and consumption sides,plays an important role in achieving carbon neutrality in China.In emerging carbon markets,assessing the investment benefits of power-grid enterprises is essential.Thus,studying the impact of the carbon market on the investment and operation of powergrid enterprises is key to ensuring their efficient operation.Notably,few studies have examined the interaction between the carbon and electricity markets using system dynamics models,highlighting a research gap in this area.This study investigates the impact of the carbon market on the investment of power-grid enterprises using a novel evaluation system based on a system dynamics model that considers carbon-emissions from an established carbon-emission accounting model.First,an index system for benefit evaluation was constructed from six aspects:financing ability,economic benefit,reliability,social responsibility,user satisfaction,and carbon-emissions.A system dynamics model was then developed to reflect the causal feedback relationship between the impact of the carbon market on the investment and operation of power-grid enterprises.The simulation results of a provincial power-grid enterprise analyze comprehensive investment evaluation benefits over a 10-year period and the impact of carbon emissions on the investment and operation of power-grid enterprises.This study provides guidelines for the benign development of power-grid enterprises within the context of the carbon market.

Pretreatment and analysis techniques development of TKIs in biological samples for pharmacokinetic studies and therapeutic drug monitoring

Tyrosine kinase inhibitors(TKIs)have emerged as the first-line small molecule drugs in many cancer therapies,exerting their effects by impeding aberrant cell growth and proliferation through the modulation of tyrosine kinase-mediated signaling pathways.However,there exists a substantial inter-individual variability in the concentrations of certain TKIs and their metabolites,which may render patients with compromised immune function susceptible to diverse infections despite receiving theoretically efficacious anticancer treatments,alongside other potential side effects or adverse reactions.Therefore,an urgent need exists for an up-to-date review concerning the biological matrices relevant to bioanalysis and the sampling methods,clinical pharmacokinetics,and therapeutic drug monitoring of different TKIs.This paper provides a comprehensive overview of the advancements in pretreatment methods,such as protein precipitation(PPT),liquid-liquid extraction(LLE),solid-phase extraction(SPE),micro-SPE(μ-SPE),magnetic SPE(MSPE),and vortex-assisted dispersive SPE(VA-DSPE)achieved since 2017.It also highlights the latest analysis techniques such as newly developed high performance liquid chromatography(HPLC)and high-resolution mass spectrometry(HRMS)methods,capillary electrophoresis(CE),gas chromatography(GC),supercritical fluid chromatography(SFC)procedures,surface plasmon resonance(SPR)assays as well as novel nanoprobes-based biosensing techniques.In addition,a comparison is made between the advantages and disadvantages of different approaches while presenting critical challenges and prospects in pharmacokinetic studies and therapeutic drug monitoring.

Advancing respirable coal mine dust source apportionment:a preliminary laboratory exploration of optical microscopy as a novel monitoring tool

Exposure to respirable coal mine dust(RCMD)can cause chronic and debilitating lung diseases.Real-time monitoring capabilities are sought which can enable a better understanding of dust components and sources.In many underground mines,RCMD includes three primary components which can be loosely associated with three major dust sources:coal dust from the coal seam itself,silicates from the surrounding rock strata,and carbonates from the inert‘rock dust’products that are applied to mitigate explosion hazards.A monitor which can reliably partition RCMD between these three components could thus allow source apportionment.And tracking silicates,specifically,could be valuable since the most serious health risks are typically associated with this component-particularly if abundant in crystalline silica.Envisioning a monitoring concept based on field microscopy,and following up on prior research using polarized light,the aim of the current study was to build and test a model to classify respirable-sized particles as either coal,silicates,or carbonates.For model development,composite dust samples were generated in the laboratory by successively depositing dust from high-purity materials onto a sticky transparent substrate,and imaging after each deposition event such that the identity of each particle was known a priori.Model testing followed a similar approach,except that real geologic materials were used as the source for each dust component.Results showed that the model had an overall accuracy of 86.5%,indicating that a field-microscopy based moni-tor could support RCMD source apportionment and silicates tracking in some coal mines.

Research on Pathways of How Digital Transformation Affects the Business Performance of MEEC Enterprises in Chengdu

This paper aims to examine the impact of digital transformations on the business performance of the meetings,expositions,events,and conventions(MEEC)industry in Chengdu by conducting an empirical analysis of 68 MEEC enterprises in the city.The study employed the fuzzy-set qualitative comparative analysis(fsQCA)method to explore the pathways and factors involved.Drawing on the theory of synergetics,nine condition variables were carefully selected from four dimensions:digital technologies,digital strategy,digital infrastructure,and digital innovation.The findings revealed that digital transformations were an intricate systematic process,whereby a single factor alone did not serve as a necessary condition for MEEC enterprises to achieve high business performance.The analysis identified five distinct pathways that would lead to high performance,which can be categorized into three distinct models:the“organization-human resources”dominated model,the“human resources-infrastructure”driven model,and the multi-factor coordination model.The analysis also identified two pathways that would result in low performance,categorized as the“basic condition absent”model.Notably,there was substantial heterogeneity observed in the configurational pathways in terms of the magnitude of the impact of digital transformation on business performance across MEEC enterprises of different sizes.This paper suggests that the government should assume the role of a platform,providing policy and financial support to MEEC enterprises to help guide them through the process of digital transformation and that MEEC enterprises themselves should seize the opportunities arising from digital transformation to strengthen their digital infrastructure construction,human resources development,and innovation in brand building.This study presents empirical evidence that contributes to the understanding of the transformation process of MEEC enterprises within the digital economy era,as well as valuable insights into understanding the channels and internal conditions involved in digital transformations.

Demography and Socio-Economic Aspects on Irrigated Smallholder Agricultural Enterprises and Their Association with the Cultivation of Maize (Zea mays L.) as a Selected Field Crop

The purpose of this study is to correlate demography and socio-economic aspects at Irrigated Smallholder Agricultural Enterprises and their association with the Cultivation of Maize in order to determine its positive impacts at irrigated smallholders’ agricultural entrepreneurs’ household. Chi-square test was used as descriptive analysis method. The Fischer Exact tests were employed to test demography (gender, age, education, and income) in winter and summer production season of irrigated smallholder agricultural enterprises and their association with the cultivation of selected field crop (i.e. maize). The results show that gender results were not being statistically significant, as measured by the Phi measure of effect size, φ = 0.149, p = 0.011, and φ = 0.05, p = 0.392 in summer. As far as age is concern, it appears to be a statistically significant association between cultivating maize and age in winter, φ = 0.046, p = 0.730 in winter and φ = 0.172, p = 0.013. Education winter result not being statistically significant, the effect size showed a weak association, as measured by the Phi measure of effect size, φ = 0.112, p = 0.305 and φ = 0.035, p = 0.948 in summer. Income result not being statistically significant, as measured by the Phi measure of effect size, φ = 0.049, p = 0.399 and φ = 0.081, p = 0.166 in summer. In conclusion, the study shows that the development of best management practices must be based on a comprehensive analysis of the livelihoods and irrigated smallholder agricultural enterprise farming styles of participating irrigated smallholder agricultural entrepreneurs.

Long-term hydrochemical monitoring and geothermometry:understanding groundwater salinization and thermal fluid contamination in Mila’s basin,Northeastern Algeria

The regular hydrochemical monitoring of groundwater in the Mila basin over an extended period has provided valuable insights into the origin of dissolved salts and the hydrogeochemical processes controlling water salinization.The data reveals that the shallow Karst aquifer shows an increase in TDS of 162 mg L^(-1) while the ther-mal carbonate aquifer that is also used for drinking water supply exhibits an increase of 178 mg L^(-1).Additionally,significant temperature variations are recorded at the sur-face in the shallow aquifers and the waters are carbo-gaseous.Analysis of dissolved major and minor elements has identified several processes influencing the chemical composition namely:dissolution of evaporitic minerals,reduction of sulphates,congruent and incongruent car-bonates’dissolution,dedolomitization and silicates’weathering.The hydrogeochemical and geothermometric results show a mixing of saline thermal water with recharge water of meteoric origin.Two main geothermalfields have been identified,a partially evolved water reservoir and a water reservoir whosefluid interacts with sulphuric acid(H_(2)S)of magmatic origin.These hot waters that are char-acterized by a strong hydrothermal alteration do ascend through faults and fractures and contribute to the contamination of shallower aquifers.Understanding the geothermometry and the hydrogeochemistry of waters is crucial for managing and protecting the quality of groundwater resources in the Mila basin,in order to ensure sustainable water supply for the region.A conceptual model for groundwater circulation and mineralization acquisition has been established to further enhance under-standing in this regard.