The future of artificial hibernation medicine:protection of nerves and organs after spinal cord injury

Spinal cord injury is a serious disease of the central nervous system involving irreversible nerve injury and various organ system injuries.At present,no effective clinical treatment exists.As one of the artificial hibernation techniques,mild hypothermia has preliminarily confirmed its clinical effect on spinal cord injury.However,its technical defects and barriers,along with serious clinical side effects,restrict its clinical application for spinal cord injury.Artificial hibernation is a futureoriented disruptive technology for human life support.It involves endogenous hibernation inducers and hibernation-related central neuromodulation that activate particular neurons,reduce the central constant temperature setting point,disrupt the normal constant body temperature,make the body adapt"to the external cold environment,and reduce the physiological resistance to cold stimulation.Thus,studying the artificial hibernation mechanism may help develop new treatment strategies more suitable for clinical use than the cooling method of mild hypothermia technology.This review introduces artificial hibernation technologies,including mild hypothermia technology,hibernation inducers,and hibernation-related central neuromodulation technology.It summarizes the relevant research on hypothermia and hibernation for organ and nerve protection.These studies show that artificial hibernation technologies have therapeutic significance on nerve injury after spinal co rd injury through inflammatory inhibition,immunosuppression,oxidative defense,and possible central protection.It also promotes the repair and protection of res pirato ry and digestive,cardiovascular,locomoto r,urinary,and endocrine systems.This review provides new insights for the clinical treatment of nerve and multiple organ protection after spinal cord injury thanks to artificial hibernation.At present,artificial hibernation technology is not mature,and research fa ces various challenges.Neve rtheless,the effort is wo rthwhile for the future development of medicine.

Chemico-biological conversion of carbon dioxide

The unabated carbon dioxide(CO_(2))emission into the atmosphere has exacerbated global climate change,resulting in extreme weather events,biodiversity loss,and an intensified greenhouse effect.To address these challenges and work toward carbon(C)neutrality and reduced CO_(2)emissions,the capture and utilization of CO_(2)have become imperative in both scientific research and industry.One cutting-edge approach to achieving efficient catalytic performance involves integrating green bioconversion and chemical conversion.This innovative strategy offers several advantages,including environmental friendliness,high efficiency,and multi-selectivity.This study provides a comprehensive review of existing technical routes for carbon sequestration(CS)and introduces two novel CS pathways:the electrochemicalbiological hybrid and artificial photosynthesis systems.It also thoroughly examines the synthesis of valuable Cnproducts from the two CS systems employing different catalysts and biocatalysts.As both systems heavily rely on electron transfer,direct and mediated electron transfer has been discussed and summarized in detail.Additionally,this study explores the conditions suitable for different catalysts and assesses the strengths and weaknesses of biocatalysts.We also explored the biocompatibility of the electrode materials and developed novel materials.These materials were specifically engineered to combine with enzymes or microbial cells to solve the biocompatibility problem,while improving the electron transfer efficiency of both.Furthermore,this review summarizes the relevant systems developed in recent years for manufacturing different products,along with their respective production efficiencies,providing a solid database for development in this direction.The novel chemical-biological combination proposed herein holds great promise for the future conversion of CO_(2)into advanced organic compounds.Additionally,it offers exciting prospects for utilizing CO_(2)in synthesizing a wide range of industrial products.Ultimately,the present study provides a unique perspective for achieving the vital goals of“peak shaving”and C-neutrality,contributing significantly to our collective efforts to combat climate change and its associated challenges.

Synthetic polymers:A review of applications in drilling fluids

With the growth of deep drilling and the complexity of the well profile,the requirements for a more complete and efficient exploitation of productive formations increase,which increases the risk of various complications.Currently,reagents based on modified natural polymers(which are naturally occurring compounds)and synthetic polymers(SPs)which are polymeric compounds created industrially,are widely used to prevent emerging complications in the drilling process.However,compared to modified natural polymers,SPs form a family of high-molecular-weight compounds that are fully synthesized by undergoing chemical polymerization reactions.SPs provide substantial flexibility in their design.Moreover,their size and chemical composition can be adjusted to provide properties for nearly all the functional objectives of drilling fluids.They can be classified based on chemical ingredients,type of reaction,and their responses to heating.However,some of SPs,due to their structural characteristics,have a high cost,a poor temperature and salt resistance in drilling fluids,and degradation begins when the temperature reaches 130℃.These drawbacks prevent SP use in some medium and deep wells.Thus,this review addresses the historical development,the characteristics,manufacturing methods,classification,and the applications of SPs in drilling fluids.The contributions of SPs as additives to drilling fluids to enhance rheology,filtrate generation,carrying of cuttings,fluid lubricity,and clay/shale stability are explained in detail.The mechanisms,impacts,and advances achieved when SPs are added to drilling fluids are also described.The typical challenges encountered by SPs when deployed in drilling fluids and their advantages and drawbacks are also discussed.Economic issues also impact the applications of SPs in drilling fluids.Consequently,the cost of the most relevant SPs,and the monomers used in their synthesis,are assessed.Environmental impacts of SPs when deployed in drilling fluids,and their manufacturing processes are identified,together with advances in SP-treatment methods aimed at reducing those impacts.Recommendations for required future research addressing SP property and performance gaps are provided.

Mapping soil organic matter in cultivated land based on multi-year composite images on monthly time scales

Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.

The occurrence,inheritance,and segregation of complex genomic structural variation in synthetic Brassica napus

"Synthetic"allopolyploids recreated by interspecific hybridization play an important role in providing novel genomic variation for crop improvement.Such synthetic allopolyploids often undergo rapid genomic structural variation(SV).However,how such SV arises,is inherited and fixed,and how it affects important traits,has rarely been comprehensively and quantitively studied in advanced generation synthetic lines.A better understanding of these processes will aid breeders in knowing how to best utilize synthetic allopolyploids in breeding programs.Here,we analyzed three genetic mapping populations(735 DH lines)derived from crosses between advanced synthetic and conventional Brassica napus(rapeseed)lines,using whole-genome sequencing to determine genome composition.We observed high tolerance of large structural variants,particularly toward the telomeres,and preferential selection for balanced homoeologous exchanges(duplication/deletion events between the A and C genomes resulting in retention of gene/chromosome dosage between homoeologous chromosome pairs),including stable events involving whole chromosomes("pseudoeuploidy").Given the experimental design(all three populations shared a common parent),we were able to observe that parental SV was regularly inherited,showed genetic hitchhiking effects on segregation,and was one of the major factors inducing adjacent novel and larger SV.Surprisingly,novel SV occurred at low frequencies with no significant impacts on observed fertility and yield-related traits in the advanced generation synthetic lines.However,incorporating genome-wide SV in linkage mapping explained significantly more genetic variance for traits.Our results provide a framework for detecting and understanding the occurrence and inheritance of genomic SV in breeding programs,and support the use of synthetic parents as an important source of novel trait variation.

A synthetic diagnostics platform for microwave imaging diagnostics in tokamaks

Interpreting experimental diagnostics data in tokamaks,while considering non-ideal effects,is challenging due to the complexity of plasmas.To address this challenge,a general synthetic diagnostics(GSD)platform has been established that facilitates microwave imaging reflectometry and electron cyclotron emission imaging.This platform utilizes plasma profiles as input and incorporates the finite-difference time domain,ray tracing and the radiative transfer equation to calculate the propagation of plasma spontaneous radiation and the external electromagnetic field in plasmas.Benchmark tests for classical cases have been conducted to verify the accuracy of every core module in the GSD platform.Finally,2D imaging of a typical electron temperature distribution is reproduced by this platform and the results are consistent with the given real experimental data.This platform also has the potential to be extended to 3D electromagnetic field simulations and other microwave diagnostics such as cross-polarization scattering.

CO_(2)capture costs of chemical looping combustion of biomass:A comparison of natural and synthetic oxygen carrier

Chemical looping combustion has the potential to be an efficient and low-cost technology capable of contributing to the reduction of the atmospheric concentration of CO_(2) in order to reach the 1.5/2°C goal and mitigate climate change.In this process,a metal oxide is used as oxygen carrier in a dual fluidized bed to generate clean CO_(2) via combustion of biomass.Most commonly,natural ores or synthetic materials are used as oxygen carrier whereas both must meet special requirements for the conversion of solid fuels.Synthetic oxygen carriers are characterized by higher reactivity at the expense of higher costs versus the lower-cost natural ores.To determine the viability of both possibilities,a techno-economic comparison of a synthetic material based on manganese,iron,and copper to the natural ore ilmenite was conducted.The synthetic oxygen carrier was characterized and tested in a pilot plant,where high combustion efficiencies up to 98.4%and carbon capture rates up to 98.5%were reached.The techno-economic assessment resulted in CO_(2) capture costs of 75 and 40€/tCO_(2) for the synthetic and natural ore route respectively,whereas a sensitivity analysis showed the high impact of production costs and attrition rates of the synthetic material.The synthetic oxygen carrier could break even with the natural ore in case of lower production costs and attrition rates,which could be reached by adapting the production process and recycling material.By comparison to state-of-the-art technologies,it is demonstrated that both routes are viable and the capture cost of CO_(2) could be reduced by implementing the chemical looping combustion technology.

Plant Nitrogen Metabolism: Balancing Resilience to Nutritional Stress andAbiotic Challenges

Plant growth and resilience to abiotic stresses,such as soil salinity and drought,depend intricately on nitrogen metabolism.This review explores nitrogen’s regulatory role in plant responses to these challenges,unveiling a dynamic interplay between nitrogen availability and abiotic stress.In the context of soil salinity,a nuanced rela-tionship emerges,featuring both antagonistic and synergistic interactions between salinity and nitrogen levels.Salinity-induced chlorophyll depletion in plants can be alleviated by optimal nitrogen supplementation;however,excessive nitrogen can exacerbate salinity stress.We delve into the complexities of this interaction and its agri-cultural implications.Nitrogen,a vital element within essential plant structures like chloroplasts,elicits diverse responses based on its availability.This review comprehensively examines manifestations of nitrogen deficiency and toxicity across various crop types,including cereals,vegetables,legumes,and fruits.Furthermore,we explore the broader consequences of nitrogen products,such as N_(2)O,NO_(2),and ammonia,on human health.Understand-ing the intricate relationship between nitrogen and salinity,especially chloride accumulation in nitrate-fed plants and sodium buildup in ammonium-fed plants,is pivotal for optimizing crop nitrogen management.However,prudent nitrogen use is essential,as overapplication can exacerbate nitrogen-related issues.Nitrogen Use Effi-ciency(NUE)is of paramount importance in addressing salinity challenges and enhancing sustainable crop productivity.Achieving this goal requires advancements in crop varieties with efficient nitrogen utilization,pre-cise timing and placement of nitrogen fertilizer application,and thoughtful nitrogen source selection to mitigate losses,particularly urea-based fertilizer volatilization.This review article delves into the multifaceted world of plant nitrogen metabolism and its pivotal role in enabling plant resilience to nutritional stress and abiotic challenges.It offers insights into future directions for sustainable agriculture.

The 2023 M_(w)6.8 Adassil Earthquake(Chichaoua,Morocco)on a steep reverse fault in the deep crust and its geodynamic implications

The Mw 6.8 Adassil earthquake that occurred in the High Atlas on September 8,2023,was a catastrophic event that provided a rare opportunity to study the mechanics of deep crustal seismicity.This research aimed to decipher the rupture characteristics of the Adassil earthquake by analyzing teleseismic waveform data in conjunction with interferometric synthetic aperture radar(InSAR)observations from both ascending and descending orbits.Our analysis revealed a reverse fault mechanism with a centroid depth of approximately 28 km,exceeding the typical range for crustal earthquakes.This result suggests the presence of cooler temperatures in the lower crust,which facilitates the accumulation of tectonic stress.The earthquake exhibited a steep reverse mechanism,dipping at 70°,accompanied by minor strike-slip motion.Within the geotectonic framework of the High Atlas,known for its volcanic legacy and resulting thermal irregularities,we investigated the potential contributions of these factors to the initiation of the Adassil earthquake.Deep seismicity within the lower crust,away from plate boundaries,calls for extensive research to elucidate its implications for regional seismic hazard assessment.Our findings highlight the critical importance of studying and preparing for significant seismic events in similar geological settings,which would provide valuable insights into regional seismic hazard assessments and geodynamic paradigms.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique

BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling technique(SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients.METHODS In this retrospective cohort study,we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022.The incidence of postoperative delirium was recorded for 7 d post-surgery.Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not.A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium.The SMOTE technique was applied to enhance the model by oversampling the delirium cases.The model’s predictive accuracy was then validated.RESULTS In our study involving 611 elderly patients with abdominal malignant tumors,multivariate logistic regression analysis identified significant risk factors for postoperative delirium.These included the Charlson comorbidity index,American Society of Anesthesiologists classification,history of cerebrovascular disease,surgical duration,perioperative blood transfusion,and postoperative pain score.The incidence rate of postoperative delirium in our study was 22.91%.The original predictive model(P1)exhibited an area under the receiver operating characteristic curve of 0.862.In comparison,the SMOTE-based logistic early warning model(P2),which utilized the SMOTE oversampling algorithm,showed a slightly lower but comparable area under the curve of 0.856,suggesting no significant difference in performance between the two predictive approaches.CONCLUSION This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods,effectively addressing data imbalance.

Epigenetic silencing schlafen-11 sensitizes esophageal cancer to ATM inhibitor

BACKGROUND Targeting DNA damage response(DDR)pathway is a cutting-edge strategy.It has been reported that Schlafen-11(SLFN11)contributes to increase chemosensitivity by participating in DDR.However,the detailed mechanism is unclear.AIM To investigate the role of SLFN11 in DDR and the application of synthetic lethal in esophageal cancer with SLFN11 defects.METHODS To reach the purpose,eight esophageal squamous carcinoma cell lines,142 esophageal dysplasia(ED)and 1007 primary esophageal squamous cell carcinoma(ESCC)samples and various techniques were utilized,including methylationspecific polymerase chain reaction,CRISPR/Cas9 technique,Western blot,colony formation assay,and xenograft mouse model.RESULTS Methylation of SLFN11 was exhibited in 9.15%of(13/142)ED and 25.62%of primary(258/1007)ESCC cases,and its expression was regulated by promoter region methylation.SLFN11 methylation was significantly associated with tumor differentiation and tumor size(both P<0.05).However,no significant associations were observed between promoter region methylation and age,gender,smoking,alcohol consumption,TNM stage,or lymph node metastasis.Utilizing DNA damaged model induced by low dose cisplatin,SLFN11 was found to activate non-homologous end-joining and ATR/CHK1 signaling pathways,while inhibiting the ATM/CHK2 signaling pathway.Epigenetic silencing of SLFN11 was found to sensitize the ESCC cells to ATM inhibitor(AZD0156),both in vitro and in vivo.CONCLUSION SLFN11 is frequently methylated in human ESCC.Methylation of SLFN11 is sensitive marker of ATM inhibitor in ESCC.

Modulated-ISRJ rejection using online dictionary learning for synthetic aperture radar imagery

In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.

High-Precision DOA Estimation Method Based on Synthetic Aperture Technique

The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to noise.In this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present signals.The concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA estimations.Moreover,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA estimations.Simulation results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).

Method of Monitoring Three-dimensional Mining Surface Deformation Based on InSAR

In order to solve the problems of small monitoring range,long time and high cost of existing sedimentation observation methods,based on two-view sentinel No.1 radar images of Guqiao mining area in Huainan City from November 4,2017 to November 28,2017,surface change information was obtained in combination with D-InSAR,and the three-dimensional surface deformation was monitored by two-pass method and single line of sight D-InSAR method.The results show that during the research period of 24 d,the maximum deformation of the mining area reached 71 mm,and the southern subsidence was the most obvious,which was in line with the mining subsidence law.The maximum displacement from the north to the south was about 250 mm,while the maximum displacement from the east to the west was about 80 mm,and the maximum subsidence in the center was 110 mm.It is concluded that D-InSAR technique has a good effect on the inversion of the mining subsidence,and this method is suitable for three-dimensional surface monitoring in areas with similar geological conditions.The monitoring results have certain reference value.

Revisiting the standards of cancer detection and therapy alongside their comparison to modern methods

In accordance with the World Health Organization data,cancer remains at the forefront of fatal diseases.An upward trend in cancer incidence and mortality has been observed globally,emphasizing that efforts in developing detection and treatment methods should continue.The diagnostic path typically begins with learning the medical history of a patient;this is followed by basic blood tests and imaging tests to indicate where cancer may be located to schedule a needle biopsy.Prompt initiation of diagnosis is crucial since delayed cancer detection entails higher costs of treatment and hospitalization.Thus,there is a need for novel cancer detection methods such as liquid biopsy,elastography,synthetic biosensors,fluorescence imaging,and reflectance confocal microscopy.Conventional therapeutic methods,although still common in clinical practice,pose many limitations and are unsatisfactory.Nowadays,there is a dynamic advancement of clinical research and the development of more precise and effective methods such as oncolytic virotherapy,exosome-based therapy,nanotechnology,dendritic cells,chimeric antigen receptors,immune checkpoint inhibitors,natural product-based therapy,tumor-treating fields,and photodynamic therapy.The present paper compares available data on conventional and modern methods of cancer detection and therapy to facilitate an understanding of this rapidly advancing field and its future directions.As evidenced,modern methods are not without drawbacks;there is still a need to develop new detection strategies and therapeutic approaches to improve sensitivity,specificity,safety,and efficacy.Nevertheless,an appropriate route has been taken,as confirmed by the approval of some modern methods by the Food and Drug Administration.

iDEAL-CIO: Instant Digital Express Advocated “Magic Lamp” for Cloud Intelligence Outlet

Instant Digital Express iDEAL-CIO The “Magic Lamp” for Cloud Intelligence Outlet, which has been recommended, combines innovations to satisfy modern users’ needs and efficiently sift through the ever-expanding amount of intelligent content stored in the cloud. One such innovation introduces a ground-breaking concept to remove superfluous and outdated sequential search patterns that overwhelm the user and computer in order to better serve the user in an eclectic & elastic and multidimensional approach to finding, grouping, assimilation, organizing, and delivering archival content. The cloud intelligence outlet (CIO) is presented in this article as the perfect magic lamp option for quick digital express advocacy. The grouping, indexing, folding, and targeting (GIFT) method of multidimensional online synthetic/analytical intelligent content (MOSAIC) for adaptive intelligence is the fundamental intelligent aggregation and automated process of the Magic Lamp. Three perspectives above this new ideal framework are available to observe: The Magic Lamp proposes contextual and multiple analytical tracks to improve cloud intelligence services conceptually. Technically speaking, MOSAIC combines domain-specific services for a wide range of international users, and through the usage of Cloud Intelligence Outlet, GIFT operationally activates grouping, indexing, folding, and targeting to promote decent experience and in-depth research on target for users’ wants. Because of this, iDEAL-CIO works in tandem with cloud extraction, digital transformation, and archival loading to provide improved service through the readily accessible cloud intelligence outlet.

Research Progress on Removal of Oxygenatesin Fischer-Tropsch Oil by Adsorption

The oxygen-containing compounds in Fischer Tropsch synthetic oil greatly affect the downstream deep processing of hydrocarbons,and effective removal is required.Com-pared to traditional removal technologies such as hydrogenation deoxygenation,solvent extraction,and extraction distillation,adsorption deoxygenation technology has the advantages of low cost,mild operating conditions,easy removal and recovery,and mini-mal impact on oil quality.Therefore,adsorption deoxygenation technology has devel-oped rapidly in various removal processes and has become a research hotspot in the cur-rent Fischer Tropsch oil deoxygenation.Adsorbents are the core of adsorption deoxygen-ation technology.Therefore,this article briefly introduces the adsorption mechanism and summarizes the research progress of adsorbents widely used in recent years,such as silica gel,alumina,molecular sieves,and metal organic frameworks,in adsorbing oxygen-containing compounds in Fischer Tropsch synthetic oils.And provide reference sugges-tions for further adsorption and deoxygenation directions in the future.

Application of Pomegranate Rind Extract for Improvement of Functional Properties of Various Materials—A Critical Review

Pomegranate rind is abundantly available as a waste material. Pomegranate Rind Extract (PRE) can be applied to cotton fabrics for its natural colours, as a mordanting agent and also for imparting certain functional properties such as fire retardancy and antimicrobial properties. This paper reviews the feasibility of Pomegranate Rind Extract to improve the functional properties of cellulosic fabrics. Studies show that varying concentrations and higher temperatures that were used to apply the extract on the fabric, resulted in enhanced functional properties. At a particular concentration, the treated fabric showed a 15 times lower burning rate in comparison with the control fabric. Also, antimicrobial efficacy has been observed against Gram-positive and Gram-negative bacteria. Due to the natural colouring material, it can be used as a natural dye on cotton material. The fire retardancy of pomegranate rind extract was tested on jute material under varying alkalinity. Research has indicated that pomegranate rind extract could be used to dye polyamide as well. The rubbing and wash fastness of the finished fabrics is good. The light fastness was fair, and its antibacterial efficiency against tested bacteria was good.

A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data

Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance.