Endoscopic diagnosis and management of gallbladder carcinoma in minimally invasive era:New needs,new models

Gallbladder cancer(GBC)is a rare and lethal malignancy;however,it represents the most common type of biliary tract cancer.Patients with GBC are often diagnosed at an advanced stage,thus,unfortunately,losing the opportunity for curative surgical intervention.This situation leads to lower quality of life and higher mortality rates.In recent years,the rapid development of endoscopic equipment and techniques has provided new avenues and possibilities for the early and minimally invasive diagnosis and treatment of GBC.This editorial comments on the article by Pavlidis et al.Building upon their work,we explore the new needs and corresponding models for managing GBC from the endoscopic diagnosis and treatment perspective.

Modeling Solid Waste Minimization Performance at Source in Dar es Salaam City, Tanzania

Municipal solid waste generation is strongly linked to rising human population and expanding urban areas, with significant implications on urban metabolism as well as space and place values redefinition. Effective management performance of municipal solid waste management underscores the interdisciplinarity strategies. Such knowledge and skills are paramount to uncover the sources of waste generation as well as means of waste storage, collection, recycling, transportation, handling/treatment, disposal, and monitoring. This study was conducted in Dar es Salaam city. Driven by the curiosity model of the solid waste minimization performance at source, study data was collected using focus group discussion techniques to ward-level local government officers, which was triangulated with literature and documentary review. The main themes of the FGD were situational factors (SFA) and local government by-laws (LGBY). In the FGD session, sub-themes of SFA tricked to understand how MSW minimization is related to the presence and effect of services such as land use planning, availability of landfills, solid waste transfer stations, material recovery facilities, incinerators, solid waste collection bins, solid waste trucks, solid waste management budget and solid waste collection agents. Similarly, FGD on LGBY was extended by sub-themes such as contents of the by-law, community awareness of the by-law, and by-law enforcement mechanisms. While data preparation applied an analytical hierarchy process, data analysis applied an ordinary least square (OLS) regression model for sub-criteria that explain SFA and LGBY;and OLS standard residues as variables into geographically weighted regression with a resolution of 241 × 241 meter in ArcMap v10.5. Results showed that situational factors and local government by-laws have a strong relationship with the rate of minimizing solid waste dumping in water bodies (local R square = 0.94).

MINIMAL FOLIATIONS FOR THE HIGH-DIMENSIONAL FRENKEL-KONTOROVA MODEL

For the high-dimensional Frenkel-Kontorova(FK)model on lattices,we study the existence of minimal foliations by depinning force.We introduce the tilted gradient flow and define the depinning force as the critical value of the external force under which the average velocity of the system is zero.Then,the depinning force can be used as the criterion for the existence of minimal foliations for the FK model on a Z^(d)lattice for d>1.

Discrimination for minimal hepatic encephalopathy based on Bayesian modeling of default mode network

In order to classify the minimal hepatic encephalopathy （MHE） patients from healthy controls, the independent component analysis （ICA） is used to generate the default mode network （DMN） from resting-state functional magnetic resonance imaging （fMRI）. Then a Bayesian voxel- wised method, graphical-model-based multivariate analysis （GAMMA）, is used to explore the associations between abnormal functional integration within DMN and clinical variable. Without any prior knowledge, five machine learning methods, namely, support vector machines （SVMs）, classification and regression trees （ CART ）, logistic regression, the Bayesian network, and C4.5, are applied to the classification. The functional integration patterns were alternative within DMN, which have the power to predict MHE with an accuracy of 98%. The GAMMA method generating functional integration patterns within DMN can become a simple, objective, and common imaging biomarker for detecting MIIE and can serve as a supplement to the existing diagnostic methods.

Modified MMS: Minimization Approach for Model Subset Selection

Considering the recent developments in the digital environment,ensuring a higher level of security for networking systems is imperative.Many security approaches are being constantly developed to protect against evolving threats.An ensemble model for the intrusion classification system yielded promising results based on the knowledge of many prior studies.This research work aimed to create a more diverse and effective ensemble model.To this end,selected six classification models,Logistic Regression(LR),Naive Bayes(NB),K-Nearest Neighbor(KNN),Decision Tree(DT),Support Vector Machine(SVM),and Random Forest(RF)from existing study to run as independent models.Once the individual models were trained,a Correlation-Based Diversity Matrix(CDM)was created by determining their closeness.The models for the ensemble were chosen by the proposed Modified Minimization Approach for Model Subset Selection(Modified-MMS)from Lower triangular-CDM(L-CDM)as input.The proposed algorithm performance was assessed using the Network Security Laboratory—Knowledge Discovery in Databases(NSL-KDD)dataset,and several performance metrics,including accuracy,precision,recall,and F1-score.By selecting a diverse set of models,the proposed system enhances the performance of an ensemble by reducing overfitting and increasing prediction accuracy.The proposed work achieved an impressive accuracy of 99.26%,using only two classification models in an ensemble,which surpasses the performance of a larger ensemble that employs six classification models.

Synchronization of the minimal models of bursting neurons coupled by delayed chemical or electrical synapses

The minimal two-dimensional model of bursting neuronal dynamics is used to study the influence of time-delay on the properties of synchronization of bursting neurons. Generic properties of bursting and dependence of the stability of synchronization on the time-lag and the strength of coupling are described, and compared with the two common types of synaptical coupling, i.e., time-delayed chemical and electrical synapses.

Adaptive enhancement design of triply periodic minimal surface lattice structure based on non-uniform stress distribution

The Schwarz primitive triply periodic minimal surface(P-type TPMS)lattice structures are widely used.However,these lattice structures have weak load-bearing capacity compared with other cellular structures.In this paper,an adaptive enhancement design method based on the non-uniform stress distribution in structures with uniform thickness is proposed to design the P-type TPMS lattice structures with higher mechanical properties.Two types of structures are designed by adjusting the adaptive thickness distribution in the TPMS.One keeps the same relative density,and the other keeps the same of non-enhanced region thickness.Compared with the uniform lattice structure,the elastic modulus for the structure with the same relative density increases by more than 17%,and the yield strength increases by more than 10.2%.Three kinds of TPMS lattice structures are fabricated by laser powder bed fusion(L-PBF)with 316L stainless steel to verify the proposed enhanced design.The manufacture-induced geometric deviation between the as-design and as-printed models is measured by micro X-ray computed tomography(μ-CT)scans.The quasi-static compression experimental results of P-type TPMS lattice structures show that the reinforced structures have stronger elastic moduli,ultimate strengths,and energy absorption capabilities than the homogeneous P-TPMS lattice structure.

Bayesian analysis of minimal model under the insulin-modified IVGTT

A Bayesian analysis of the minimal model was proposed where both glucose and insulin were analyzed simultaneously under the insulin-modified intravenous glucose tolerance test (IVGTT). The resulting model was implemented with a nonlinear mixed-effects modeling setup using ordinary differential equations (ODEs), which leads to precise estimation of population parameters by separating the inter- and intra-individual variability. The results indicated that the Bayesian method applied to the glucose-insulin minimal model provided a satisfactory solution with accurate parameter estimates which were numerically stable since the Bayesian method did not require approximation by linearization.

R-Parity Violation Effects on b_1 → bχ_1~0 in Minimal SupersymmetricStandard Model

We investigate in detail the effects of R-parity lepton number violation onthe decay b_1 → bχ_1~0 in the R-parity violating minimal supersymmetric standard model (R_p-MSSM)under the present experimental constraints on R_p parameters. In our numerical calculations weconsider two cases of input parameters of the squark and slepton sectors, M_(squark) 【 M_(slepton)and M_(squark) 】 M_(slepton), for comparison. The results show that the relative R-parity violatingcorrection is not very sensitive to the mass of the lightest neutralino bχ_1~0 the degenerateR-parity violating coupling parameter λ′_2 but strongly depends on M_(squark), M_(slepton) tan βand tie degenerate R-parity violating coupling parameter λ′_1. The relative correction is about -4～ 3% and can exceed -6% in some region of parameter space. Therefore, precise experiment analyseson the decay b_1 → bχ_1~0 may provide a probe of the R-parity violation.

Solution of Modified Bergman Minimal Blood Glucose-Insulin Model Using Caputo-Fabrizio Fractional Derivative

Diabetes is a burning issue in the whole world.It is the imbalance between body glucose and insulin.The study of this imbalance is very much needed from a research point of view.For this reason,Bergman gave an important model named-Bergman minimalmodel.In the present work,using Caputo-Fabrizio(CF)fractional derivative,we generalize Bergman’s minimal blood glucose-insulin model.Further,we modify the old model by including one more component known as diet D(t),which is also essential for the blood glucose model.We solve the modified modelwith the help of Sumudu transformand fixed-point iteration procedures.Also,using the fixed point theorem,we examine the existence and uniqueness of the results along with their numerical and graphical representation.Furthermore,the comparison between the values of parameters obtained by calculating different values of t with experimental data is also studied.Finally,we draw the graphs of G(t),X(t),I(t),andD(t)for different values ofτ.It is also clear from the obtained results and their graphical representation that the obtained results of modified Bergman’s minimal model are better than Bergman’s model.

Calculation of Particle Decay Times in the Standard Model

We present here a two-step method of classification and calculation for decay rates in the Standard Model. The first step is a phenomenological classification method, which is an extended and improved schematic experimental formula for decay width originally introduced by Chang. This schematic formula separates decays into seven classes. Furthermore, from it is derived a process-specific interaction energy mX. The second step is a numerical calculation method, which calculates this interaction energy mX numerically by minimization of action from the Lagrangian of the process, from which follows the decay width via the phenomenological formula. The Lagrangian is based on an extension of the Standard Model, the extended SU(4)-preon-model. A comparison of numerically calculated and observed decay widths for a large selection of decays shows a good agreement.

Early Water Quality Modeling with Minimal Data to Support Management Decisions： A Case Study of Aguamilpa Reservoir

This paper presents a case study that demonstrates how models can be used to support water management decisions before sufficient data to verify the model are available. In developing areas, and for new reservoirs, extensive data for model calibration and validation are often not available. As a case study we developed a CE-QUAL-W2 model of Aguamilpa Reservoir using minimal data and used the model to create a data acquisition plan to support early planning decisions. We based the model on a two-year period and compared the model results to data recently collected with our acquisition plan. We present how we developed and used the model to design the data acquisition plan which identifies and collects data to update and calibrate the model to support future decisions. We show that a minimally calibrated model based on scarce data can support management decisions and be the first step in a spiral engineering approach to system management. Spiral engineering uses models and data to both support early decisions and to iteratively improve this information to support subsequent decisions and models. This case study can be used as a guide for developing water quality models with minimal data and uses the models to support early decision requirements.

Calculation of the Standard Model Parameters and Particles Based on a SU(4) Preon Model

This paper describes an extension and a new foundation of the Standard Model of particle physics based on a SU(4)-force called hyper-color, and on preon subparticles. The hyper-color force is a generalization of the SU(2)-based weak interaction and the SU(1)-based right-chiral self-interaction, in which the W-and the Z-bosons are Yukawa residual-field-carriers of the hyper-color force, in the same sense as the pions are the residual-field-carriers of the color SU(3) interaction. Using the method of numerical minimization of the SU(4)-action based on this model, the masses and the inner structure of leptons, quarks and weak bosons are calculated: the mass results are very close to the experimental values. We calculate also precisely the value of the Cabibbo angle, so the mixing matrices of the Standard model, CKM matrix for quarks and PMNS matrix for neutrinos can also be calculated. In total, we reduce the 29 parameters of the Standard Model to a total of 7 parameters.

Minimal Realization of Linear Graph Models for Multi-physics Systems

An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.The present paper concerns the use of linear graphs(LGs)to generate a minimal model for a multi-physics system.A state-space model has to be a minimal realization.Specifically,the number of state variables in the model should be the minimum number that can completely represent the dynamic state of the system.This choice is not straightforward.Initially,state variables are assigned to all the energy-storage elements of the system.However,some of the energy storage elements may not be independent,and then some of the chosen state variables will be redundant.An approach is presented in the paper,with illustrative examples in the mixed fluid-mechanical domains,to illustrate a way to recognize dependent energy storage elements and thereby obtain a minimal state-space model.System analysis in the frequency domain is known to be more convenient than in the time domain,mainly because the relevant operations are algebraic rather than differential.For achieving this objective,the state space model has to be converted into a transfer function.The direct way is to first convert the state-space model into the input-output differential equation,and then substitute the time derivative by the Laplace variable.This approach is shown in the paper.The same result can be obtained through the transfer function linear graph(TF LG)of the system.In a multi-physics system,first the physical domains have to be converted into an equivalent single domain(preferably,the output domain of the system),when using the method of TFLG.This procedure is illustrated as well,in the present paper.

Computational evaluation of the dynamic minimal model for the root causes of hypoglycemia

This research is an attempt to validate how glu-cose-insulin dynamic mathematical model facilitate to identify the root causes for hypoglycaemia. The purpose is to determine whether increased insulin sensitivity or increased insulin secretion causes post- prandial hypoglycemic (PPH) response, by linking experimental patient data with dynamic mathematical model. For this purpose two groups, as hypoglycemic Group 1 and non-hypoglycemic Group 2, each of which consists of 10 people, are formed. The oral glucose tolerance test (OGTT) is carried out for each person in the groups by measuring plasma glucose and insulin concentrations at every 30 minutes for a period of 5 hours. To distinguish the actual cause of hypoglycemia, the glucose minimal dynamic model is used. The model is executed in MATLAB platform using patient data and the results showed that insulin secretion is assumed to be the potential root cause for the hypoglycemia.

95 GeV light Higgs in the top-pair-associated diphoton channel at the LHC in the minimal dilaton model

Motivated by experimental hints and theoretical frameworks indicating the existence of an extended Higgs sector,we explore the feasibility of detecting a 95 GeV light Higgs boson decaying into a diphoton within the minimal dilaton model at the 14 TeV LHC.Initially,we identify the correlations between the production cross section,decay branching ratios,and model parameters,e.g.,the scalar mixing angle■Subsequently,we utilize Monte Carlo simulations to generate the signal of the light Higgs boson via the■process,along with the corresponding backgrounds.To effectively separate the signal from the dominant backgrounds■,we employ a meticulous cut-based selection process.Ultimately,we find that with an integrated luminosity of L=3000fb^(-1),the regions of■can be covered over the3σlevel.

Reversibility of minimal hepatic encephalopathy following liver transplantation in Egyptian cirrhotic patients

AIMTo evaluate the reversibility of minimal hepatic encephalopathy (MHE) following liver transplantation (LT) in Egyptian cirrhotic patients. METHODSThis prospective study included twenty patients with biopsy-proven liver cirrhosis listed for LT and twenty age- and sex-matched healthy control subjects. All underwent neuro-psychiatric examination, laboratory investigations, radiological studies and psychometric tests including trail making test A (TMT A), TMT B, digit symbol test and serial dotting test. The psychometric hepatic encephalopathy score (PHES) was calculated for patients to diagnose MHE. Psychometric tests were repeated six months following LT in the cirrhotic patient group. RESULTSBefore LT, psychometric tests showed highly significant deficits in cirrhotic patients in comparison to controls (P P P P = 0.005). More patients in whom reversal of MHE was observed had a pre-transplant MELD score CONCLUSIONReversal of MHE in cirrhotic patients could be achieved by LT, especially in those with a MELD score

Lymph node metastasis in early gastric cancer with submucosal invasion:Feasibility of minimally invasive surgery

AIM:To explore the feasibility of pertorming minimally invasive surgery(MIS)on subsets of submucosal gastric cancers that are unlikely to have regional lymph node metastasis. METHODS:A total of 105 patients underwent radical gastrectomy with lymph node dissection for submucosal gastric cancer at our hospital from January 1995 to December 1995.Besides investigating many clinicopathological features such as tumor size,gross appearance,and differentiation, we measured the depth of invasion into submucosa minutely and analyzed the clinicopathologic features of these patients regarding lymph node metastasis. RESULTS:The rate of lymph node metastasis in cases where the depth of invasion was<500 μm,500-2 000 μm,or >2 000 μm was 9%(2/23),19%(7136),and 33%(15/46), respectively(P<0.05).In univariate analysis,no significant correlation was found between lymph node metastasis and clinicopathological characteristics such as age,sex,tumor location,gross appearance,tumor differentiation,Lauren's classification,and lymphatic invasion.In multivariate analysis, tumor size(>4 cm vs≤2 cm,odds ratio=4.80, P=0.04)and depth of invasion(>2 000 μm vs ≤500 μm, odds ratio=6.81,P=0.02)were significantly correlated with lymph node metastasis.Combining the depth and size in cases where the depth of invasion was less than 500 μm, we found that lymph node metastasis occurred where the tumor size was greater than 4 cm.In cases where the tumor size was less than 2 cm,lymph node metastasis was found only where the depth of tumor invasion was more than 2 000 μm. CONCLUSION:MIS can be applied to submucosal gastric cancer that is less than 2 cm in size and 500 μm in depth.

Effect of minimal shoes and slope on vertical and leg stiffness during running

Purpose： This study was designed to characterize and compare the vertical（kvert） and leg（kleg） stiffness measured during running in two different footwear conditions on negative, level, and positive slopes, using kinematic data only.Methods： Fourteen male recreational runners（age 23.4 4.4 years, height 177.5 5.2 cm, and body mass 69.5 5.3 kg） were tested on 2separate days within 1 week. At each session, subjects ran seven 5-min trials on a treadmill at 10 km/h, interspersed with 5 min of sitting passive recovery. Each trial was performed on a different slope gradient, ranging from 8%（downhill） to t8%（uphill）, assigned in a random order.Furthermore, each subject ran one 5-min trial wearing minimal shoes（MS） and the subsequent trial wearing traditional shoes（TS） in a counterbalanced randomized order ensuring that each slope was ran once in MS and once in TS. Kinematic data were collected using a photocell measuring system and high-speed video camera, with kvertand klegstiffness being calculated from these data.Results： Leg compression, contact times, and vertical displacement of the center of mass during running were significantly smaller in MS compared to TS across all slopes. In the two footwear conditions, step frequency significantly increased with a（positive） increase in slope.Kinematic analyses indicated that klegwas greater when running in MS than TS and this between-footwear difference remained similar across slopes. On the contrary, kvertdid not change on the basis of footwear, but increased with positive increases in slope.Conclusion： This study showed that kvertand klegduring running respond differently to change in footwear and/or slope. These two stiffness measures can hence provide a unique insight on the biomechanical adaptations of running under varying conditions and their respective quantification may assist in furthering our understanding of training, performance, and/or injury in this sport.

A constructive approach to minimal realization problem of 2D systems

Unlike in the 1D case, it is not always possible to find a minimal state-space realization for a 2D system except for some particular categories. The purpose of this paper is to explore a constructive approach to the minimal Roesser model realization problem for a class of 2D systems which does not belong to the clarified categories. As one of the main results, a constructive realization procedure is first proposed. Based on the proposed procedure, sufficient conditions and explicit construction for minimal realizations of the considered 2D systems are shown. In addition, possible variations and applications of the obtained results are discussed and illustrative examples are presented.