Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia

Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive task.Many researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir heterogeneity.However,these attributes take seismic data as input and might not be sensitive to lateral lithology variation.To incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance inversion.Our proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as input.To evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,Australia.This study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional approach.In addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir characterization.This study also suggests a well-bounded potential reservoir facies distribution along the parallel fault lines.Thus,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage.

Surgical strategies for challenging common bile duct stones in the endoscopic era: A comprehensive review of current evidence

While endoscopic retrograde cholangiopancreatography(ERCP)remains the primary treatment modality for common bile duct stones(CBDS)or choledocho-lithiasis due to advancements in instruments,surgical intervention,known as common bile duct exploration(CBDE),is still necessary in cases of difficult CBDS,failed endoscopic treatment,or altered anatomy.Recent evidence also supports CBDE in patients requesting single-step cholecystectomy and bile duct stone removal with comparable outcomes.This review elucidates relevant clinical anatomy,selection indications,and outcomes to enhance surgical understanding.The selection between trans-cystic(TC)vs trans-choledochal(TD)approaches is described,along with stone removal techniques and ductal closure.Detailed surgical techniques and strategies for both the TC and TD approaches,including instrument selection,is also provided.Additionally,this review comprehensively addresses operation-specific complications such as bile leakage,stricture,and entrapment,and focuses on preventive measures and treatment strategies.This review aims to optimize the management of CBDS through laparoscopic CBDE,with the goal of improving patient outcomes and minimizing risks.

Distal-scanning common path probe for optical coherence tomography

In this paper,we present a distal-scanning common path probe for optical coherence tomography(OCT)equipped with a hollow ultrasonic motor and a simple and specially designed beam-splitter.This novel probe proves to be able to effectively circumvent polarization and dispersion mismatch caused by fiber motion and is more robust to a variety of interfering factors during the imaging process,experimentally compared to a conventional noncommon path probe.Furthermore,our design counteracts the attenuation of backscattering with depth and the fall-off of the signal,resulting in a more balanced signal range and greater imaging depth.Spectral-domain OCT imaging of phantom and biological tissue is also demonstrated with a sensitivity of∼100dB and a lateral resolution of∼3μm.This low-cost probe offers simplified system configuration and excellent robustness,and is therefore particularly suitable for clinical diagnosis as one-off medical apparatus.

Transverse mode-coupling instability with longitudinal impedance

Transverse mode-coupling instability(TMCI)is a dangerous transverse single-bunch instability that can lead to severe par-ticle loss.The mechanism of TMCI can be explained by the coupling of transverse coherent oscillation modes owing to the transverse short-range wakefield(i.e.,the transverse broadband impedance).Recent studies on future circular colliders,e.g.,FCC-ee,showed that the threshold of TMCI decreased significantly when both longitudinal and transverse impedances were included.We performed computations for the circular electron-positron collider(CEPC)and observed a similar phenom-enon.Systematic studies on the influence of longitudinal impedance on the TMCI threshold were conducted.We concluded that the imaginary part of the longitudinal impedance,which caused a reduction in the incoherent synchrotron tune,was the primary reason for the reduction in the TMCI threshold.Additionally,the real part of the longitudinal impedance assists in increasing the TMCI threshold.

Do brood parasitic Common Cuckoos develop brood patches during the breeding season?

Many birds develop brood patches on their ventral apterium under hormonal regulation to effectively transmit body heat to eggs during incubation.The developed patch has several characteristics,including de-feathering,vascularization,and edema.However,little is known about whether avian brood parasites that do not incubate their eggs exhibit brood patch development during the breeding season.In this study,we measured the size of the ventral apterium in 114 Common Cuckoos(Cuculus canorus)captured in the field throughout the breeding season and examined the appearance of the ventral apterium to confirm the development of brood patches.We also examined whether morphological traits and various factors correlated with the size of the ventral apterium(sternal apterium and abdominal apterium)and how it changed during the breeding season.We found no clear signs of brood patch development in Common Cuckoos captured throughout the breeding season,indicating that they likely did not develop brood patches on the ventral apterium during this period.We also found that ventral apterium size was positively correlated with wing length and body weight.In addition,Common Cuckoos with newly growing feathers on the boundary of the ventral apterium with pteryla were frequently observed as seasons progressed to the end.In conclusion,Common Cuckoos exhibit neither brood patch development nor the vestigial characteristics of ancestral brood patches,except for the growth of feathers on boundary the ventral apterium.Further studies examining brood patches across different groups of avian brood parasites are valuable for enhancing our understanding of the developmental and physiological adaptations of avian brood parasites.

Novel method for identifying the stages of discharge underwater based on impedance change characteristic

It is difficult to determine the discharge stages in a fixed time of repetitive discharge underwater due to the arc formation process being susceptible to external environmental influences. This paper proposes a novel underwater discharge stage identification method based on the Strong Tracking Filter(STF) and impedance change characteristics. The time-varying equivalent circuit model of the discharge underwater is established based on the plasma theory analysis of the impedance change characteristics and mechanism of the discharge process. The STF is used to reduce the randomness of the impedance of repeated discharges underwater, and then the universal identification resistance data is obtained. Based on the resistance variation characteristics of the discriminating resistance of the pre-breakdown, main, and oscillatory discharge stages, the threshold values for determining the discharge stage are obtained. These include the threshold values for the resistance variation rate(K) and the moment(t).Experimental and error analysis results demonstrate the efficacy of this innovative method in discharge stage determination, with a maximum mean square deviation of Scrless than 1.761.

Results of Surgical Management of Malignant Obstruction of the Common Bile Duct in Yaoundé

Introduction: In Cameroon, surgery remains the only approach in malignant obstructions of the common bile duct (MOCBD) even in palliative situations. The aim of this work was to describe the modalities of surgical treatment of MOCBD, evaluate the results and detect the factors associated with postoperative morbidity and mortality. Patients and Methods: We conducted an analytical observational study, with retrospective data collection from the files of patients operated upon for MOCBD. This was done in four referral hospitals in the city of Yaoundé for a 42-month period spanning from January 1, 2020 to June 30, 2023. Demographic data, clinical presentation, surgical data, and 30-day postoperative outcomes were collected. Results: We collected 71 files. The sex ratio was 1.4 and the mean age was 56 ± 11 years. Fifty-three (53) patients (74.6%) were overweight or obese and 10 patients (14.1%) were hypertensive. A clinical cholestasis syndrome was present in 69 patients (97.2%). Fifty-five (55) patients (77.5%) had a cancer of the head of the pancreas, 8 patients (11.3%) had an extra-hepatic cholangiocarcinoma and 8 patients (11.3%) had an ampullary adenocarcinoma. Eight (8) resections (11.3%) with curative intent had been carried out and in 63 cases (88.7%), surgery was palliative. Postoperative morbidity was 55.7%, influenced by advanced WHO stage (p = 0.02). Postoperative mortality was 25.7%, associated with a high ASA score (p = 0.01). Conclusion: Pancreatic head cancer is the main etiology of malignant obstructions of the common bile duct in Cameroon. Surgical treatment is most often palliative. Postoperative morbidity and mortality are high, influenced by high WHO and ASA scores.

Construction of a broadband impedance spectrum and synchronous DC voltammetry measurement system for solar cells

The current impedance spectroscopy measurement techniques face difficulties in diagnosing solar cell faults due to issues such as cost,complexity,and accuracy.Therefore,a novel system was developed for precise broadband impedance spectrum measurement of solar cells,which was composed of an oscilloscope,a signal generator,and a sampling resistor.The results demonstrate concurrent accurate measurement of the impedance spectrum(50 Hz-0.1 MHz)and direct current voltametric characteristics.Comparative analysis with Keithley 2450 data yields a global relative error of approximately 6.70%,affirming the accuracy.Among excitation signals(sine,square,triangle,pulse waves),sine wave input yields the most accurate data,with a root mean square error of approximately 13.3016 and a global relative error of approximately 4.25%compared to theoretical data.Elevating reference resistance expands the half circle in the impedance spectrum.Proximity of reference resistance to that of the solar cell enhances the accuracy by mitigating line resistance influence.Measurement error is lower in high-frequency regions due to a higher signal-to-noise ratio.

Oriental Reed Warblers do not abandon Common Cuckoo chicks during prolonged nestling periods

The Oriental Reed Warbler(Acrocephalus orientalis)is one of the most commonly used hosts for the parasitic Common Cuckoo(Cuculus canorus).However,as hosts that feed unrelated parasitic nestlings may suffer extra reproductive costs,they may be less willing to care for nestlings that have prolonged nestling periods.To test this hypothesis,the duration of feeding by Oriental Reed Warblers under natural conditions for their own nestlings was compared with the duration of feeding under natural conditions for Common Cuckoo nestlings and for artificially prolonged cuckoo nestlings.The results showed that Oriental Reed Warblers did not starve,drive away,or desert any of the nestlings in the experiment,and neither parent was left alone.Our experimental study indicates that both Oriental Reed Warbler parents were willing to care for nestlings with a prolonged nestling period(up to 30 days,twice the average duration time that the Oriental Reed Warblers fed their own chicks in natural conditions).However,further experiments and observations are required in other host bird species to examine whether both parents or one of the parents may exhibit the behavior of abandoning nestlings with a prolonged nestling period.

Predicting dynamic compressive strength of frozen-thawed rocks by characteristic impedance and data-driven methods

In cold regions,the dynamic compressive strength(DCS)of rock damaged by freeze-thaw weathering significantly influences the stability of rock engineering.Nevertheless,testing the dynamic strength under freeze-thaw weathering conditions is often both time-consuming and expensive.Therefore,this study considers the effect of characteristic impedance on DCS and aims to quickly determine the DCS of frozen-thawed rocks through the application of machine-learning techniques.Initially,a database of DCS for frozen-thawed rocks,comprising 216 rock specimens,was compiled.Three external load parameters(freeze-thaw cycle number,confining pressure,and impact pressure)and two rock parameters(characteristic impedance and porosity)were selected as input variables,with DCS as the predicted target.This research optimized the kernel scale,penalty factor,and insensitive loss coefficient of the support vector regression(SVR)model using five swarm intelligent optimization algorithms,leading to the development of five hybrid models.In addition,a statistical DCS prediction equation using multiple linear regression techniques was developed.The performance of the prediction models was comprehensively evaluated using two error indexes and two trend indexes.A sensitivity analysis based on the cosine amplitude method has also been conducted.The results demonstrate that the proposed hybrid SVR-based models consistently provided accurate DCS predictions.Among these models,the SVR model optimized with the chameleon swarm algorithm exhibited the best performance,with metrics indicating its effectiveness,including root mean square error(RMSE)﹦3.9675,mean absolute error(MAE)﹦2.9673,coefficient of determination(R^(2))﹦0.98631,and variance accounted for(VAF)﹦98.634.This suggests that the chameleon swarm algorithm yielded the most optimal results for enhancing SVR models.Notably,impact pressure and characteristic impedance emerged as the two most influential parameters in DCS prediction.This research is anticipated to serve as a reliable reference for estimating the DCS of rocks subjected to freeze-thaw weathering.

Data-driven diagnosis of high temperature PEM fuel cells based on the electrochemical impedance spectroscopy: Robustness improvement and evaluation

Utilizing machine learning techniques for data-driven diagnosis of high temperature PEM fuel cells is beneficial and meaningful to the system durability. Nevertheless, ensuring the robustness of diagnosis remains a critical and challenging task in real application. To enhance the robustness of diagnosis and achieve a more thorough evaluation of diagnostic performance, a robust diagnostic procedure based on electrochemical impedance spectroscopy (EIS) and a new method for evaluation of the diagnosis robustness was proposed and investigated in this work. To improve the diagnosis robustness: (1) the degradation mechanism of different faults in the high temperature PEM fuel cell was first analyzed via the distribution of relaxation time of EIS to determine the equivalent circuit model (ECM) with better interpretability, simplicity and accuracy;(2) the feature extraction was implemented on the identified parameters of the ECM and extra attention was paid to distinguishing between the long-term normal degradation and other faults;(3) a Siamese Network was adopted to get features with higher robustness in a new embedding. The diagnosis was conducted using 6 classic classification algorithms—support vector machine (SVM), K-nearest neighbor (KNN), logistic regression (LR), decision tree (DT), random forest (RF), and Naive Bayes employing a dataset comprising a total of 1935 collected EIS. To evaluate the robustness of trained models: (1) different levels of errors were added to the features for performance evaluation;(2) a robustness coefficient (Roubust_C) was defined for a quantified and explicit evaluation of the diagnosis robustness. The diagnostic models employing the proposed feature extraction method can not only achieve the higher performance of around 100% but also higher robustness for diagnosis models. Despite the initial performance being similar, the KNN demonstrated a superior robustness after feature selection and re-embedding by triplet-loss method, which suggests the necessity of robustness evaluation for the machine learning models and the effectiveness of the defined robustness coefficient. This work hopes to give new insights to the robust diagnosis of high temperature PEM fuel cells and more comprehensive performance evaluation of the data-driven method for diagnostic application.

Mean nocturnal baseline impedance in gastro-esophageal reflux disease diagnosis:Should we strictly follow the Lyon 2 Consensus?

Clinical practice guidelines drive clinical practice and clinicians rely to them when trying to answer their most common questions.One of the most important position papers in the field of gastro-esophageal reflux disease(GERD)is the one produced by the Lyon Consensus.Recently an updated second version has been released.Mean nocturnal baseline impedance(MNBI)was proposed by the first Consensus to act as supportive evidence for GERD diagnosis.Originally a cut-off of 2292 Ohms was proposed,a value revised in the second edition.The updated Consensus recommended that an MNBI<1500 Ohms strongly suggests GERD while a value>2500 Ohms can be used to refute GERD.The proposed cut-offs move in the correct direction by diminishing the original cut-off,nevertheless they arise from a study of normal subjects where cut-offs were provided by measuring the mean value±2SD and not in symptomatic patients.However,data exist that even symptomatic patients with inconclusive disease or reflux hypersensitivity(RH)show lower MNBI values in comparison to normal subjects or patients with functional heartburn(FH).Moreover,according to the data,MNBI,even among symptomatic patients,is affected by age and body mass index.Also,various studies have proposed different cut-offs by using receiver operating characteristic curve analysis even lower than the one proposed.Finally,no information is given for patients submitted to on-proton pump inhibitors pH-impedance studies even if new and extremely important data now exist.Therefore,even if MNBI is an extremely important tool when trying to approach patients with reflux symptoms and could distinguish conclusive GERD from RH or FH,its values should be interpreted with caution.

Digital Infrastructure and Common Prosperity: An Influence Mechanism and Effect Test

Common prosperity is an important goal of China’s modernization efforts,and narrowing the income gap among different regions and populations is crucial to achieving common prosperity.The construction of digital infrastructure has significantly boosted productivity and facilitated the diffusion of technology in less developed regions,leading to notable changes in labor employment and the income gap,which aligns with the goal of common prosperity.This paper explores the mechanism through which digital infrastructure influences common prosperity with a focus on employment,using panel data from 30 provinces in China between 2011 and 2021 for an empirical test.The research finds that digital infrastructure significantly promotes common prosperity.By expanding employment and increasing labor remuneration,the influence of digital infrastructure on common prosperity exhibits regional heterogeneity and a nonlinear threshold effect.The research suggests that the government should enhance investment in and construction of digital infrastructure,reduce the digital divide through policy support in rural areas,promote digital employment and skills training,and encourage industrial integration and enterprise participation.

Solid-state impedance spectroscopy studies of dielectric properties and relaxation processes in Na_(2)O–V_(2)O_(5)–Nb_(2)O_(5)–P_(2)O_(5) glass

Solid-state impedance spectroscopy(SS-IS)was used to investigate the influence of structural modifications resulting from the addition of Nb2O5 on the dielectric properties and relaxation processes in the quaternary mixed glass former(MGF)system 35Na_(2)O–10V_(2)O_(5)–(55-x)P_(2)O_(5)–xNb_(2)O_(5)(x=0–40,mol%).The dielectric parameters,including the dielectric strength and dielectric loss,are determined from the frequency and temperature-dependent complex permittivity data,revealing a significant dependence on the Nb2O5 content.The transition from a predominantly phosphate glass network(x<10,region I)to a mixed niobate–phosphate glass net-work(10≤x≤20,region II)leads to an increase in the dielectric parameters,which correlates with the observed trend in the direct-cur-rent(DC)conductivity.In the predominantly niobate network(x≥25,region III),the highly polarizable nature of Nb5+ions leads to a fur-ther increase in the dielectric permittivity and dielectric strength.This is particularly evident in Nb-40 glass-ceramic,which contains Na_(13)Nb_(35)O_(94) crystalline phase with a tungsten bronze structure and exhibits the highest dielectric permittivity of 61.81 and the lowest loss factor of 0.032 at 303 K and 10 kHz.The relaxation studies,analyzed through modulus formalism and complex impedance data,show that DC conductivity and relaxation processes are governed by the same mechanism,attributed to ionic conductivity.In contrast to glasses with a single peak in frequency dependence of imaginary part of electrical modulus,M″(ω),Nb-40 glass-ceramic exhibits two distinct contributions with similar relaxation times.The high-frequency peak indicates bulk ionic conductivity,while the additional low-fre-quency peak is associated with the grain boundary effect,confirmed by the electrical equivalent circuit(EEC)modelling.The scaling characteristics of permittivity and conductivity spectra,along with the electrical modulus,validate time-temperature superposition and demonstrate a strong correlation with composition and modification of the glass structure upon Nb_(2)O_(5) incorporation.

Accelerating the Digitalization Process in Rural China and Promoting Common Prosperity

Under the historical background of promoting agricultural and rural modernization in an all-round way,this paper deeply analyzes the practical significance of digital construction in rural China,and explores the problems in the digitalization level of rural infrastructure,farmers digitalization awareness and accomplishment,and agricultural digital system.Countermeasures and suggestions are put forward from four aspects:digital village construction policy system,rural digital infrastructure construction,rural digital talent cultivation system,and agricultural digital system,and the rural digital construction of Huzhou City is taken as an example,in order to further realize the goal of empowering rural farmers with digital technology for common prosperity.

Improved reservoir characterization by means of supervised machine learning and model-based seismic impedance inversion in the Penobscot field,Scotian Basin

The present research work attempted to delineate and characterize the reservoir facies from the Dawson Canyon Formation in the Penobscot field,Scotian Basin.An integrated study of instantaneous frequency,P-impedance,volume of clay and neutron-porosity attributes,and structural framework was done to unravel the Late Cretaceous depositional system and reservoir facies distribution patterns within the study area.Fault strikes were found in the EW and NEE-SWW directions indicating the dominant course of tectonic activities during the Late Cretaceous period in the region.P-impedance was estimated using model-based seismic inversion.Petrophysical properties such as the neutron porosity(NPHI)and volume of clay(VCL)were estimated using the multilayer perceptron neural network with high accuracy.Comparatively,a combination of low instantaneous frequency(15-30 Hz),moderate to high impedance(7000-9500 gm/cc*m/s),low neutron porosity(27%-40%)and low volume of clay(40%-60%),suggests fair-to-good sandstone development in the Dawson Canyon Formation.After calibration with the welllog data,it is found that further lowering in these attribute responses signifies the clean sandstone facies possibly containing hydrocarbons.The present study suggests that the shale lithofacies dominates the Late Cretaceous deposition(Dawson Canyon Formation)in the Penobscot field,Scotian Basin.Major faults and overlying shale facies provide structural and stratigraphic seals and act as a suitable hydrocarbon entrapment mechanism in the Dawson Canyon Formation's reservoirs.The present research advocates the integrated analysis of multi-attributes estimated using different methods to minimize the risk involved in hydrocarbon exploration.

Undifferentiated high-grade pleomorphic sarcoma of the common bile duct:A case report and review of literature

BACKGROUND Undifferentiated pleomorphic sarcoma(UPS)is a rare malignant mesenchymal tumor with a poor prognosis.It mainly occurs in the extremities,trunk,head and neck,and retroperitoneum regions.Owing to the lack of specific clinical manifestations and imaging features,UPS diagnosis mainly depends on pathological and immunohistochemical examinations for exclusive diagnosis.Here we report an extremely rare case of high-grade UPS in the common bile duct(CBD).There are limited available data on such cases.CASE SUMMARY A 70-year-old woman was admitted to our department with yellow eyes and urine accompanied by upper abdominal distending pain for 2 wk.Her laboratory data suggested significantly elevated hepatorenal function levels.The imaging data revealed calculous cholecystitis,intrahepatic and extrahepatic bile duct dilation with extrahepatic bile duct calculi,and a space-occupying lesion at the distal CBD.After endoscopic biliary stenting and symptomatic support therapy,CBD exploration and biopsy were performed.The frozen section indicated malignant spindle cell tumor of the CBD mass,and further radical pancreaticoduodenectomy was performed.Finally,the neoplasm was diagnosed as a high-grade UPS combined with the light-microscopic morphology and immunohistochemical results.CONCLUSION This extremely rare case highlighted the need for increasing physicians'vigilance,reducing the odds of misdiagnosis,and providing appropriate treatment strategies.

Security Vulnerability Analyses of Large Language Models (LLMs) through Extension of the Common Vulnerability Scoring System (CVSS) Framework

Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, and more. However, their widespread usage emphasizes the critical need to enhance their security posture to ensure the integrity and reliability of their outputs and minimize harmful effects. Prompt injections and training data poisoning attacks are two of the most prominent vulnerabilities in LLMs, which could potentially lead to unpredictable and undesirable behaviors, such as biased outputs, misinformation propagation, and even malicious content generation. The Common Vulnerability Scoring System (CVSS) framework provides a standardized approach to capturing the principal characteristics of vulnerabilities, facilitating a deeper understanding of their severity within the security and AI communities. By extending the current CVSS framework, we generate scores for these vulnerabilities such that organizations can prioritize mitigation efforts, allocate resources effectively, and implement targeted security measures to defend against potential risks.