Search results for: drug release model

Authors: Mohsen Ziaee

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In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.

Keywords: scheduling, flexible job shop, makespan, mixed integer linear programming

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Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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Authors: Ravisinh Solanki, Ravi Patel, Chhaganbhai Patel

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Purpose: The purpose of this study is to develop a methodology for the risk assessment and evaluation of nitrosamine impurities in Glipizide antidiabetic formulations. Nitroso compounds, including nitrosamines, have emerged as significant concerns in drug products, as highlighted by the ICH M7 guidelines. This study aims to identify known and potential sources of nitrosamine impurities that may contaminate Glipizide formulations and assess their presence. By determining observed or predicted levels of these impurities and comparing them with regulatory guidance, this research will contribute to ensuring the safety and quality of combination antidiabetic drug products on the market. Factors contributing to the presence of genotoxic nitrosamine contaminants in glipizide medications, such as secondary and tertiary amines, and nitroso group-complex forming molecules, will be investigated. Additionally, conditions necessary for nitrosamine formation, including the presence of nitrosating agents, and acidic environments, will be examined to enhance understanding and mitigation strategies. Method: The methodology for the study involves the implementation of the N-Nitroso Acid Precursor (NAP) test, as recommended by the WHO in 1978 and detailed in the 1980 International Agency for Research on Cancer monograph. Individual glass vials containing equivalent to 10mM quantities of Glipizide is prepared. These compounds are dissolved in an acidic environment and supplemented with 40 mM NaNO2. The resulting solutions are maintained at a temperature of 37°C for a duration of 4 hours. For the analysis of the samples, an HPLC method is employed for fit-for-purpose separation. LC resolution is achieved using a step gradient on an Agilent Eclipse Plus C18 column (4.6 X 100 mm, 3.5µ). Mobile phases A and B consist of 0.1% v/v formic acid in water and acetonitrile, respectively, following a gradient mode program. The flow rate is set at 0.6 mL/min, and the column compartment temperature is maintained at 35°C. Detection is performed using a PDA detector within the wavelength range of 190-400 nm. To determine the exact mass of formed nitrosamine drug substance related impurities (NDSRIs), the HPLC method is transferred to LC-TQ-MS/MS with the same mobile phase composition and gradient program. The injection volume is set at 5 µL, and MS analysis is conducted in Electrospray Ionization (ESI) mode within the mass range of 100−1000 Daltons. Results: The samples of NAP test were prepared according to the protocol. The samples were analyzed using HPLC and LC-TQ-MS/MS identify possible NDSRIs generated in different formulations of glipizide. It was found that the NAP test generated a various NDSRIs. The new finding, which has not been reported yet, discovered contamination of Glipizide. These NDSRIs are categorised based on the predicted carcinogenic potency and recommended its acceptable intact in medicines. The analytical method was found specific and reproducible.

Keywords: NDSRI, nitrosamine impurities, antidiabetic, glipizide, LC-MS/MS

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Authors: Alija Uzunovic, Sasa Pilipovic, Aida Sapcanin, Zahida Ademovic, Berina Pilipović

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Capsaicin is a naturally occurring alkaloid extracted from capsicum fruit extracts of different of Capsicum species. It has been employed topically to treat many diseases such as rheumatoid arthritis, osteoarthritis, cancer pain and nerve pain in diabetes. The high degree of pre-systemic metabolism of intragastrical capsaicin and the short half-life of capsaicin by intravenous administration made topical application of capsaicin advantageous. In this study, we have evaluated differences in the dissolution characteristics of capsaicin patch 11 mg (purchased from market) at different dissolution rotation speed. The proposed patch area is 308 cm2 (22 cm x 14 cm; it contains 36 µg of capsaicin per square centimeter of adhesive). USP Apparatus 5 (Paddle Over Disc) is used for transdermal patch testing. The dissolution study was conducted using USP apparatus 5 (n=6), ERWEKA DT800 dissolution tester (paddle-type) with addition of a disc. The fabricated patch of 308 cm2 is to be cut into 9 cm2 was placed against a disc (delivery side up) retained with the stainless-steel screen and exposed to 500 mL of phosphate buffer solution pH 7.4. All dissolution studies were carried out at 32 ± 0.5 °C and different rotation speed (50± 5; 100± 5 and 150± 5 rpm). 5 ml aliquots of samples were withdrawn at various time intervals (1, 4, 8 and 12 hours) and replaced with 5 ml of dissolution medium. Withdrawn were appropriately diluted and analyzed by reversed-phase liquid chromatography (RP-LC). A Reversed Phase Liquid Chromatography (RP-LC) method has been developed, optimized and validated for the separation and quantitation of capsaicin in a transdermal patch. The method uses a ProntoSIL 120-3-C18 AQ 125 x 4,0 mm (3 μm) column maintained at 600C. The mobile phase consisted of acetonitrile: water (50:50 v/v), the flow rate of 0.9 mL/min, the injection volume 10 μL and the detection wavelength 222 nm. The used RP-LC method is simple, sensitive and accurate and can be applied for fast (total chromatographic run time was 4.0 minutes) and simultaneous analysis of capsaicin and dihydrocapsaicin in a transdermal patch. According to the results obtained in this study, we can conclude that the relative difference of dissolution rate of capsaicin after 12 hours was elevated by increase of dissolution rotation speed (100 rpm vs 50 rpm: 84.9± 11.3% and 150 rpm vs 100 rpm: 39.8± 8.3%). Although several apparatus and procedures (USP apparatus 5, 6, 7 and a paddle over extraction cell method) have been used to study in vitro release characteristics of transdermal patches, USP Apparatus 5 (Paddle Over Disc) could be considered as a discriminatory test. would be able to point out the differences in the dissolution rate of capsaicin at different rotation speed.

Keywords: capsaicin, in vitro, patch, RP-LC, transdermal

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Authors: Gang Liu, Can Wang, Runnan Zhang, Quan Wang, Huimin Song, Shaomin Ji

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Biba model can protect information integrity but might deny various non-malicious access requests of the subjects, thereby decreasing the availability in the system. Therefore, a mechanism that allows exceptional access control is needed. Break the Glass (BTG) strategies refer an efficient means for extending the access rights of users in exceptional cases. These strategies help to prevent a system from stagnation. An approach is presented in this work for integrating Break the Glass strategies into the Biba model. This research proposes a model, BTG-Biba, which provides both an original Biba model used in normal situations and a mechanism used in emergency situations. The proposed model is context aware, can implement a fine-grained type of access control and primarily solves cross-domain access problems. Finally, the flexibility and availability improvement with the use of the proposed model is illustrated.

Keywords: Biba model, break the glass, context, cross-domain, fine-grained

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

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Authors: Nicolas Giraudo, Peter Thissen

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In this paper we bring up new aspects of the metal proton exchange reaction (MPER, also called early stage hydration): (1) its dependence of the number of protons consumed by the preferential exchanged cations on the pH value applied at the water/wollastonite interface and (2) strong anisotropic characteristics detected in atomic force microscopy (AFM) and low energy ion scattering spectroscopy measurements (LEIS). First we apply density functional theory (DFT) calculations to compare the kinetics of the reaction on different wollastonite surfaces, and combine it with ab initio thermodynamics to set up a model describing (1) the release of Ca in exchange with H coming from the water/wollastonite interface, (2) the dependence of the MPER on the chemical potential of protons. In the second part of the paper we carried out in-situ AFM and inductive coupled plasma atomic emission spectroscopy (ICP-OES) measurements in order to evaluate the predicted values. While a good agreement is found in the basic and neutral regime (pH values from 14-4), an increasing mismatch appears in the acidic regime (pH value lower 4). This is finally explained by non-equilibrium etching, dominating over the MPER in the very acidic regime.

Keywords: anisotropy, calcium silicate, cement, density functional theory, hydration

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Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

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Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

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Authors: Deepak Mohan, Sushma Sharma, Mohammad Asif

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Diclofenac sodium being one of the most common non-steroidal anti-inflammatory drugs is normally used as painkiller and to reduce inflammation. The drug is known to alter the enzymatic activities of acid and alkaline phosphatase, glutamate oxaloacetate transaminase and glutamate pyruvate transaminases. The drug also results in change in the concentration of proteins and lipids in the body. The present study is an attempt to study different biochemical changes electrophoretically due to administration of different doses of diclofenac (4mg/kg/body weight and 14mg/kg/body weight) on liver and testes of mice from 7-28 days of investigation. Homogenization of the tissue was done, supernatant separated was loaded in the gel and native polyacrylamide gel electrophoresis was conducted. Diclofenac administration resulted in alterations of all these biochemical parameters which were observed in native polyacrylamide gel electrophoretic studies. The severe degenerative changes as observed during later stages of the experiment showed correlation with increase or decrease in the activities of all the enzymes studied in the present investigation. Image analysis of gel in liver showed a decline of 7.4 and 5.3 % in low and high dose group after 7 days whereas a decline of 9.6 and 7.5% was registered after 28 days of investigation. Similar analysis for testis also showed an appreciable decline in the activity of alkaline phosphatase after 28 days. Gel analysis of serum was also performed to find a correlation in the enzymatic activities between the tissue and blood.

Keywords: diclofenac, inflammation, polyacrylamide, phosphatase

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Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

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Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

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Authors: Julia Kapr, Andrea Rossi, Haribaskar Ramachandran, Marius Pollet, Ilka Egger, Selina Dangeleit, Katharina Koch, Jean Krutmann, Ellen Fritsche

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It is widely acknowledged that animal models do not always represent human disease. Especially human brain development is difficult to model in animals due to a variety of structural and functional species-specificities. This causes significant discrepancies between predicted and apparent drug efficacies in clinical trials and their subsequent failure. Emerging alternatives based on 3D in vitro approaches, such as human brain spheres or organoids, may in the future reduce and ultimately replace animal models. Here, we present a human induced pluripotent stem cell (hiPSC)-based 3D neural in a vitro disease model for the Cockayne Syndrome B (CSB). CSB is a rare hereditary disease and is accompanied by severe neurologic defects, such as microcephaly, ataxia and intellectual disability, with currently no treatment options. Therefore, the aim of this study is to investigate the molecular and cellular defects found in neural hiPSC-derived CSB models. Understanding the underlying pathology of CSB enables the development of treatment options. The two CSB models used in this study comprise a patient-derived hiPSC line and its isogenic control as well as a CSB-deficient cell line based on a healthy hiPSC line (IMR90-4) background thereby excluding genetic background-related effects. Neurally induced and differentiated brain sphere cultures were characterized via RNA Sequencing, western blot (WB), immunocytochemistry (ICC) and multielectrode arrays (MEAs). CSB-deficiency leads to an altered gene expression of markers for autophagy, focal adhesion and neural network formation. Cell migration was significantly reduced and electrical activity was significantly increased in the disease cell lines. These data hint that the cellular pathologies is possibly underlying CSB. By induction of autophagy, the migration phenotype could be partially rescued, suggesting a crucial role of disturbed autophagy in defective neural migration of the disease lines. Altered autophagy may also lead to inefficient mitophagy. Accordingly, disease cell lines were shown to have a lower mitochondrial base activity and a higher susceptibility to mitochondrial stress induced by rotenone. Since mitochondria play an important role in neurotransmitter cycling, we suggest that defective mitochondria may lead to altered electrical activity in the disease cell lines. Failure to clear the defective mitochondria by mitophagy and thus missing initiation cues for new mitochondrial production could potentiate this problem. With our data, we aim at establishing a disease adverse outcome pathway (AOP), thereby adding to the in-depth understanding of this multi-faced disorder and subsequently contributing to alternative drug development.

Keywords: autophagy, disease modeling, in vitro, pluripotent stem cells

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Authors: Shabnum Shaheen, Nida Haroon, Farah Khan, Sumera Javad, Mehreen Jalal, Samina Sarwar

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Coffee Senna is pharmaceutically very important and used for multiple health disorders such as gastric pains, indigestion, snakebites, asthma and fever, tuberculosis and menstrual problems. However, its immense medicinal value and great demand lead to adulteration issue which could be injurious for users. Some times its adulterant Seena weed (Senna occidentalis L.) is used as its substitute which definitely not as effective as Coffee Senna. Hence, the present study was undertaken to provide some tools for systematic and pharmaceutical authentication of a shrubby plant Coffee Senna (Cassia occidentalis Linn.). These parameters included macro and micro morphological characters, anatomical and palynomorph characterization, solubility, fluorescence and phytochemical analysis. By the application of these parameters acquired results revealed that, these two plants are distinct from each other. The Coffee Seena was found to be an annual shrub with trilobed pollen, diacytic, paracytic and anisocytic stomata whereas the Seena weed stands out as an annual or perennial herb with spheroidal and circular pollen and paracytic type of stomata. The powdered drug of Coffee seena is dark grayish green whereas the powdered drug of Seena weed is light green in color. These findings are constructive in authentic identification of these plants.

Keywords: coffee senna, Senna weed, taxonomic evaluation, pharmaceutical markers

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Authors: Athmane Bakhta, Sebastien Leclaire, David Vidal, Francois Bertrand, Mohamed Cheriet

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This work presents a new three-dimensional variational model proposed for the simulation of ink seepage into paper sheets at the fiber level. The model, inspired by the Hising model, takes into account a finite volume of ink and describes the system state through gravity, cohesion, and adhesion force interactions. At the mesoscopic scale, the paper substrate is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Besides, a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters, and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles.

Keywords: fibrous media, lattice Boltzmann, modelling and simulation, Monte Carlo, variational model

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Authors: Avinash Chaudhary, Akhilesh Gupta, Surendra Kumar, Ravi Kumar

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This paper presents the numerical study on Jatropha oil pool fire in a compartment. A fire experiment with jatropha oil was conducted in a compartment of size 4 m x 4 m x m to study the fire development and temperature distribution. Fuel is burned in the center of the compartment in a pool diameter of 0.5 m with an initial fuel depth of 0.045 m. Corner temperature in the compartment, doorway temperature and hot gas layer temperature at various locations are measured. Numerical simulations were carried out using Fire Dynamics Simulator (FDS) software at grid size of 0.05 m, 0.12 m and for performing simulation heat release rate of jatropha oil measured using mass loss method were inputted into FDS. Experimental results shows that like other fuel fires, the whole combustion process can be divided into four stages: initial stage, growth stage, steady profile or developed phase and decay stage. The fire behavior shows two zone profile where upper zone consists of mainly hot gases while lower zone is relatively at colder side. In this study, predicted temperatures from simulation are in good agreement in upper zone of compartment. Near the interface of hot and cold zone, deviations were reported between the simulated and experimental results which is probably due to the difference between the predictions of smoke layer height by FDS. Also, changing the grid size from 0.12 m to 0.05 m does not show any effect in temperatures at upper zone while in lower zone, grid size of 0.05 m showed satisfactory agreement with experimental results. Numerical results showed that calculated temperatures at various locations matched well with the experimental results. On the whole, an effective method is provided with reasonable results to study the burning characteristics of jatropha oil with numerical simulations.

Keywords: jatropha oil, compartment fire, heat release rate, FDS (fire dynamics simulator), numerical simulation

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Authors: Suparman

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Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: piecewise regression, bayesian, reversible jump MCMC, segmentation

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Authors: Shirin Jalili, Sadegh Hasannia, Hadi Shirzad, Afshin Khara

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Morphine is one of the most medicinally important analgesics and narcotics. Structurally, it is classified as an alkaloid because of the presence of nitrogen. Its structure is similar to that of codeine, thebaine, and heroin. An immunoassay to accurately discriminate between these analogous alkaloids would be highly beneficial. A key factor for such an assay is specificity with high sensitivity, which is totally dependent on the antibody employed. However, most antibodies against haptens are polyclonal serum antibodies that exhibit significant cross-reactivities with closely related compounds. The camel-derived single-chain antibody fragments (VHH) are the smallest molecules with antigen-binding capacity, possessing unique properties compared to other conventional antibodies. In this study, a library containing the VHH genes of a camel immunized with with morphine conjugated BSA following phage display technology was generated. By screening the camel-derived variable region of the heavy chain cDNA phage display library with the ability to bind the desired hapten, we obtained some nanobodies that recognize this hapten. Phage display expression of the Nbs from this library and pannings against this hapten resulted in a clear enrichment of four distinct Nb-displaying phages with specificity for morphine that could be a potential target site for the development of new strategies for the development of a biosensor for detecting illicit drug.

Keywords: phage display, nanobody, Morphine-3, glucuronide, ELISA, biosensor

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Authors: Batuhan Kocaoglu

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Although using powerful systems like ERP (Enterprise Resource Planning), companies still cannot benchmark their processes and measure their process performance easily based on predefined SCOR (Supply Chain Operation References) terms. The purpose of this research is to identify common and corresponding processes to present a conceptual model to model and measure the purchasing process of an organization. The main steps for the research study are: Literature review related to 'procure to pay' process in ERP system; Literature review related to 'sourcing' process in SCOR model; To develop a conceptual model integrating 'sourcing' of SCOR model and 'procure to pay' of ERP model. In this study, we examined the similarities and differences between these two models. The proposed framework is based on the assumptions that are drawn from (1) the body of literature, (2) the authors’ experience by working in the field of enterprise and logistics information systems. The modeling framework provides a structured and systematic way to model and decompose necessary information from conceptual representation to process element specification. This conceptual model will help the organizations to make quality purchasing system measurement instruments and tools. And offered adaptation issues for ERP systems and SCOR model will provide a more benchmarkable and worldwide standard business process.

Keywords: SCOR, ERP, procure to pay, sourcing, reference model

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Authors: Zahid Manzoor, Shaukat Hussain Munawar, Zahid Iqbal, Imran Ahmad Khan, Abdul Aziz, Hafiz Muhammad Qasim

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The present study was aimed to investigate the pharmacokinetics behavior and optimal dosage regimen of danofloxacin in 8 adult healthy buffaloes of local breed (Nili Ravi) following single intravenous administration at the dose of 2.5 mg/kg body weight. Plasma drug concentrations at various time intervals were measured by HPLC method. In vitro plasma protein binding was determined employing the ultrafiltration technique. The distribution and elimination of danofloxacin was rapid, as indicated by the values (Mean±SD) of distribution half-life (t1/2α = 0.25±0.09 hours) and elimination half life (t1/2β = 3.26±0.43 hours), respectively. Volume of distribution at steady state (Vss) was 1.14±0.12 L/kg, displaying its extensive distribution into various body fluids and tissues. The high value of AUC (9.80±2.14 µg/ml.hr) reflected the vast area of the body covered by drug concentration. The mean residence time was noted to be 4.78±0.52 hours. On the basis of pharmacokinetic parameters, a suitable intravenous regimen for danofloxacin in adult buffaloes would be 6.5 mg/kg to be repeated after 12 hours intervals. The present study is the foremost pharmacokinetic study of danofloxacin in the local species which would provide the valueable contribution in the local manufacturing of danofloxacin in Pakistan in future.

Keywords: danofloxacin, pharmacokinetics, plasma protein binding, buffaloes, dosage regimen

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Authors: M. Kumpugdee-Vollrath, T. G. D. Phu, M. Helmis

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A suitable model membrane to study the pharmacological effect of pharmaceutical products is human stratum corneum because this layer of human skin is the outermost layer and it is an important barrier to be passed through. Other model membranes which were also used are for example skins from pig, mouse, reptile or fish. We are interested in fish skins in this project. The advantages of the fish skins are, that they can be obtained from the supermarket or fish shop. However, the fish skins should be freshly prepared and used directly without storage. In order to understand the effect of different model drugs e.g. lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid on the properties of the model membrane from various types of fishes e.g. trout, salmon, cod, plaice permeation tests were performed and differential scanning calorimetry was applied.

Keywords: fish skin, model membrane, permeation, DSC, lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid

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Authors: Rahele Mosleh

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This paper gives a survey of results on global stability of extended Ross model for malaria by constructing some elegant Lyapunov functions for two cases of epidemic, including disease-free and endemic occasions. The model is a nonlinear seven-dimensional system of ordinary differential equations that simulates this phenomenon in a more realistic fashion. We discuss the existence of positive disease-free and endemic equilibrium points of the model. It is stated that extended Ross model possesses invariant solutions for human and mosquito in a specific domain of the system.

Keywords: global stability, invariant solutions, Lyapunov function, stationary points

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Authors: Samia A. El-Fiky, F. A. Abou-Zaid, Ibrahim M. Farag, Naira M. Efiky

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Clomipramine hydrochloride is one of the most used tricyclic antidepressant drug in Egypt. This drug contains in its chemical structure on two benzene rings. Benzene is considered to be toxic and clastogenic agent. So, the present study was designed to assess the genotoxic effect of Clomipramine hydrochloride on somatic and germ cells in mice. Three dose levels 0.195 (Low), 0.26 (Medium), and 0.65 (High) mg/kg.b.wt. were used. Seven groups of male mice were utilized in this work. The first group was employed as a control. In the remaining six groups, each of the above doses was orally administrated for two groups, one of them was treated for 5 days and the other group was given the same dose for 30 days. At the end of experiments, the animals were sacrificed for cytogenetic and sperm examination as well as histopathological investigations by using hematoxylin and eosin stains (H and E stains) and electron microscope. Concerning the sperm studies, these studies were confined to 5 days treatment with different dose levels. Moreover, the ultrastructural investigation by electron microscope was restricted to 30 days treatment with drug doses. The results of the dose dependent effect of Clomipramine showed that the treatment with three different doses induced increases of frequencies of chromosome aberrations in bone marrow and spermatocyte cells as compared to control. In addition, mitotic and meiotic activities of somatic and germ cells were declined. The treatments with medium or high doses were more effective for inducing significant increases of chromosome aberrations and significant decreases of cell divisions than treatment with low dose. The effect of high dose was more pronounced for causing such genetic deleterious in respect to effect of medium dose. Moreover, the results of the time dependent effect of Clomipramine observed that the treatment with different dose levels for 30 days led to significant increases of genetic aberrations than treatment for 5 days. Sperm examinations revealed that the treatment with Clomipramine at different dose levels caused significant increase of sperm shape abnormalities and significant decrease in sperm count as compared to control. The adverse effects on sperm shape and count were more obviousness by using the treatments with medium or high doses than those found in treatment with low dose. The group of mice treated with high dose had the highest rate of sperm shape abnormalities and the lowest proportion of sperm count as compared to mice received medium dose. In histopathological investigation, hematoxylin and eosin stains showed that, the using of low dose of Clomipramine for 5 or 30 days caused a little pathological changes in liver tissue. However, using medium and high doses for 5 or 30 days induced severe damages than that observed in mice treated with low dose. The treatment with high dose for 30 days gave the worst results of pathological changes in hepatic cells. Moreover, ultrastructure examination revealed, the mice treated with low dose of Clomipramine had little differences in liver histological architecture as compared to control group. These differences were confined to cytoplasmic inclusions. Whereas, prominent pathological changes in nuclei as well as dilated of rough Endoplasmic Reticulum (rER) were observed in mice treated with medium or high doses of Clomipramine drug. In conclusion, the present study adds evidence that treatments with medium or high doses of Clomipramine have genotoxic effects on somatic and germ cells of mice, as unwanted side effects. However, the using of low dose (especially for short time, 5 days) can be utilized as a therapeutic dose, where it caused relatively similar proportions of genetic, sperm, and histopathological changes as those found in normal control.

Keywords: clomipramine, mice, chromosome aberrations, sperm abnormalities, histopathology

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Authors: Sina Saadati, Mohammadreza Razzazi

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Since Java is an object-oriented language, It can be used to solve a wide range of problems. One of the considerable usages of this language can be found in Agent-based modeling and simulation. Despite the significant power of Java, There is not an easy method to render a 3-dimensional human model. In this article, we are about to develop a library which helps modelers present a 3D human model and control it with Java. The library runs two server programs. The first one is a web page server that can connect to any browser and present an HTML code. The second server connects to the browser and controls the movement of the model. So, the modeler will be able to develop a simulation and display a good-looking human model without any knowledge of any graphical tools.

Keywords: agent-based modeling and simulation, human model, graphics, Java, distributed systems

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Authors: Marthella Rivera Roidatua

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Since the release of Convention on the Rights of Persons with Disabilities in 2006, disability became a mainstreamed global issue. Many developed countries have shown the continuous effort to improve their disability employment policy, for example, the US and the UK with their integrated support system through disability benefits. Relative little recent research on developing country is available. Surprisingly, Indonesia, just enacted the Law No.8/2016 on Disability that bravely highlighted on integrating disabled people into the workforce. It shows a positive progress shifting traditional perspective to what Tom Shakespeare’s concept of a social model of disability. But, the main question is how can this law support the disabled people to access and maintain paid work. Thus, besides the earlier literature reviews, interviews with leading sectors, Ministry of Social Affairs and Ministry of Manpower, was conducted to examine government’s attitude towards the disabled worker. Insights from two local social enterprises on disability were also engaged in building better perspective. The various source of data was triangulated then analysed with a thematic approach. Results were encouraging the Indonesian government to have a better collaboration with other impactful local organisations in promoting the disability employment. In the end, this paper also recommends the government to make a reasonable adjustment and practical guideline for companies in hiring disabled.

Keywords: disability, employment, policy, Indonesia, collaboration, guidelines

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Authors: Semra Çoruh, Yusuf Tibet

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Dyes are widely used in industries such as textiles, paper, paints, leather, rubber, plastics, cosmetics, food, and drug etc, to color their products. Due to their chemical structures, dyes are resistant to fading on exposure to light, water and many chemicals and, therefore, are difficult to be decolorized once released into the aquatic environment. Many of the organic dyes are hazardous and may affect aquatic life and even the food chain. This study deals with the adsorption of malachite green dye onto fly ash and red mud. The effects of experimental factors (adsorbent dosage, initial concentration, pH and temperature) on the adsorption process were examined by using 24 full factorial design. The results were statistically analyzed by using the student’s t-test, analysis of variance (ANOVA) and an F-test to define important experimental factors and their levels. A regression model that considers the significant main and interaction effects was suggested. The results showed that initial dye concentration an pH is the most significant factor that affects the removal of malachite green.

Keywords: malachite green, adsorption, red mud, fly ash, full factorial design

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Authors: Maryam Ziaee, Himanshu Shee, Amrik Sohal

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Big Data Analytics (BDA) in supply chain management has recently drawn the attention of academics and practitioners. Big data refers to a massive amount of data from different sources, in different formats, generated at high speed through transactions in business environments and supply chain networks. Traditional statistical tools and techniques find it difficult to analyse this massive data. BDA can assist organisations to capture, store, and analyse data specifically in the field of supply chain. Currently, there is a paucity of research on BDA in the pharmaceutical supply chain context. In this research, the Australian pharmaceutical supply chain was selected as the case study. This industry is highly significant since the right medicine must reach the right patients, at the right time, in right quantity, in good condition, and at the right price to save lives. However, drug shortages remain a substantial problem for hospitals across Australia with implications on patient care, staff resourcing, and expenditure. Furthermore, a massive volume and variety of data is generated at fast speed from multiple sources in pharmaceutical supply chain, which needs to be captured and analysed to benefit operational decisions at every stage of supply chain processes. As the pharmaceutical industry lags behind other industries in using BDA, it raises the question of whether the use of BDA can improve transparency among pharmaceutical supply chain by enabling the partners to make informed-decisions across their operational activities. This presentation explores the impacts of BDA on supply chain management. An exploratory qualitative approach was adopted to analyse data collected through interviews. This study also explores the BDA potential in the whole pharmaceutical supply chain rather than focusing on a single entity. Twenty semi-structured interviews were undertaken with top managers in fifteen organisations (five pharmaceutical manufacturers, five wholesalers/distributors, and five public hospital pharmacies) to investigate their views on the use of BDA. The findings revealed that BDA can enable pharmaceutical entities to have improved visibility over the whole supply chain and also the market; it enables entities, especially manufacturers, to monitor consumption and the demand rate in real-time and make accurate demand forecasts which reduce drug shortages. Timely and precise decision-making can allow the entities to source and manage their stocks more effectively. This can likely address the drug demand at hospitals and respond to unanticipated issues such as drug shortages. Earlier studies explore BDA in the context of clinical healthcare; however, this presentation investigates the benefits of BDA in the Australian pharmaceutical supply chain. Furthermore, this research enhances managers’ insight into the potentials of BDA at every stage of supply chain processes and helps to improve decision-making in their supply chain operations. The findings will turn the rhetoric of data-driven decision into a reality where the managers may opt for analytics for improved decision-making in the supply chain processes.

Keywords: big data analytics, data-driven decision, pharmaceutical industry, supply chain management

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Authors: Klazina T. Havinga, Hilde R. H. de Geus

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Introduction: Pre-operative coagulation management of Apixaban prescribed patients, a new oral anticoagulant (a factor Xa inhibitor), is difficult, especially when chronic kidney disease (CKD) causes drug overdose. Apixaban is not dialyzable due to its high level of protein binding. An antidote, Andexanet α, is available but expensive and has an unfavorable short half-life. We report the successful extracorporeal removal of Apixaban prior to emergency surgery with the CytoSorb® Hemoadsorption device. Methods: A 89-year-old woman with CKD, with an Apixaban prescription for atrial fibrillation, was presented at the ER with traumatic rib fractures, a flail chest, and an unstable spinal fracture (T12) for which emergency surgery was indicated. However, due to very high Apixaban levels, this surgery had to be postponed. Based on the Apixaban-specific anti-factor Xa activity (AFXaA) measurements at admission and 10 hours later, complete clearance was expected after 48 hours. In order to enhance the Apixaban removal and reduce the time to operation, and therefore reduce pulmonary complications, CRRT with CytoSorb® cartridge was initiated. Apixaban-specific anti-factor Xa activity (AFXaA) was measured frequently as a substitute for Apixaban drug concentrations, pre- and post adsorber, in order to calculate the adsorber-related clearance. Results: The admission AFXaA concentration, as a substitute for Apixaban drug levels, was 218 ng/ml, which decreased to 157 ng/ml after ten hours. Due to sustained anticoagulation effects, surgery was again postponed. However, the AFXaA levels decreased quickly to sub-therapeutic levels after CRRT (Multifiltrate Pro, Fresenius Medical Care, Blood flow 200 ml/min, Dialysate Flow 4000 ml/h, Prescribed renal dose 51 ml-kg-h) with Cytosorb® connected in series into the circuit was initiated (within 5 hours). The adsorber-related (indirect) Apixaban clearance was calculated every half hour (Cl=Qe * (AFXaA pre- AFXaA post/ AFXaA pre) with Qe=plasma flow rate calculated with Ht=0.38 and system blood flow rate 200 ml-min): 100 ml/min, 72 ml/min and 57 ml/min. Although, as expected, the adsorber-related clearance decreased quickly due to saturation of the beads, still the reduction rate achieved resulted in a very rapid decrease in AFXaA levels. Surgery was ordered and possible within 5 hours after Cytosorb initiation. Conclusion: The CytoSorb® Hemoadsorption device enabled rapid correction of Apixaban associated anticoagulation.

Keywords: Apixaban, CytoSorb, emergency surgery, Hemoadsorption

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Authors: Aussara Panya, Nunghathai Sawasdee, Mutita Junking, Chatchawan Srisawat, Kiattawee Choowongkomon, Pa-Thai Yenchitsomanus

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Dengue virus (DENV) infection is a global public health problem with approximately 100 million infected cases a year. Presently, there is no approved vaccine or effective drug available; therefore, the development of anti-DENV drug is urgently needed. The clinical reports revealing the positive association between the disease severity and viral titer has been reported previously suggesting that the anti-DENV drug therapy can possibly ameliorate the disease severity. Although several anti-DENV agents showed inhibitory activities against DENV infection, to date none of them accomplishes clinical use in the patients. The surface envelope (E) protein of DENV is critical for the viral entry step, which includes attachment and membrane fusion; thus, the blocking of envelope protein is an attractive strategy for anti-DENV drug development. To search the safe anti-DENV agent, this study aimed to search for novel peptide inhibitors to counter DENV infection through the targeting of E protein using a structure-based in silico design. Two selected strategies has been used including to identify the peptide inhibitor which interfere the membrane fusion process whereby the hydrophobic pocket on the E protein was the target, the destabilization of virion structure organization through the disruption of the interaction between the envelope and membrane proteins, respectively. The molecular docking technique has been used in the first strategy to search for the peptide inhibitors that specifically bind to the hydrophobic pocket. The second strategy, the peptide inhibitor has been designed to mimic the ectodomain portion of membrane protein to disrupt the protein-protein interaction. The designed peptides were tested for the effects on cell viability to measure the toxic to peptide to the cells and their inhibitory assay to inhibit the DENV infection in Vero cells. Furthermore, their antiviral effects on viral replication, intracellular protein level and viral production have been observed by using the qPCR, cell-based flavivirus immunodetection and immunofluorescence assay. None of tested peptides showed the significant effect on cell viability. The small peptide inhibitors achieved from molecular docking, Glu-Phe (EF), effectively inhibited DENV infection in cell culture system. Its most potential effect was observed for DENV2 with a half maximal inhibition concentration (IC50) of 96 μM, but it partially inhibited other serotypes. Treatment of EF at 200 µM on infected cells also significantly reduced the viral genome and protein to 83.47% and 84.15%, respectively, corresponding to the reduction of infected cell numbers. An additional approach was carried out by using peptide mimicking membrane (M) protein, namely MLH40. Treatment of MLH40 caused the reduction of foci formation in four individual DENV serotype (DENV1-4) with IC50 of 24-31 μM. Further characterization suggested that the MLH40 specifically blocked viral attachment to host membrane, and treatment with 100 μM could diminish 80% of viral attachment. In summary, targeting the hydrophobic pocket and M-binding site on the E protein by using the peptide inhibitors could inhibit DENV infection. The results provide proof of-concept for the development of antiviral therapeutic peptide inhibitors to counter DENV infection through the use of a structure-based design targeting conserved viral protein.

Keywords: dengue virus, dengue virus infection, drug design, peptide inhibitor

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Authors: Sundaram Arulmozhiraja, Kanade Shimizu, Yuta Yamamoto, Satoshi Ichikawa, Maenaka Katsumi, Hiroaki Tokiwa

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Drug discovery is shifting from small molecule based drugs targeting local active site to middle molecules (MM) targeting large, flat, and groove-shaped binding sites, for example, protein-protein interface because at least half of all targets assumed to be involved in human disease have been classified as “difficult to drug” with traditional small molecules. Hence, MMs such as peptides, natural products, glycans, nucleic acids with various high potent bioactivities become important targets for drug discovery programs in the recent years as they could be used for ‘undruggable” intracellular targets. Cell membrane permeability is one of the key properties of pharmacodynamically active MM drug compounds and so evaluating this property for the potential MMs is crucial. Computational prediction for cell membrane permeability of molecules is very challenging; however, recent advancement in the molecular dynamics simulations help to solve this issue partially. It is expected that MMs with high membrane permeability will enable drug discovery research to expand its borders towards intracellular targets. Further to understand the chemistry behind the permeability of MMs, it is necessary to investigate their conformational changes during the permeation through membrane and for that their interactions with the membrane field should be studied reliably because these interactions involve various non-bonding interactions such as hydrogen bonding, -stacking, charge-transfer, polarization dispersion, and non-classical weak hydrogen bonding. Therefore, parameters-based classical mechanics calculations are hardly sufficient to investigate these interactions rather, quantum mechanical (QM) calculations are essential. Fragment molecular orbital (FMO) method could be used for such purpose as it performs ab initio QM calculations by dividing the system into fragments. The present work is aimed to study the cell permeability of middle molecules using molecular dynamics simulations and FMO-QM calculations. For this purpose, a natural compound syringolin and its analogues were considered in this study. Molecular simulations were performed using NAMD and Gromacs programs with CHARMM force field. FMO calculations were performed using the PAICS program at the correlated Resolution-of-Identity second-order Moller Plesset (RI-MP2) level with the cc-pVDZ basis set. The simulations clearly show that while syringolin could not permeate the membrane, its selected analogues go through the medium in nano second scale. These correlates well with the existing experimental evidences that these syringolin analogues are membrane-permeable compounds. Further analyses indicate that intramolecular -stacking interactions in the syringolin analogues influenced their permeability positively. These intramolecular interactions reduce the polarity of these analogues so that they could permeate the lipophilic cell membrane. Conclusively, the cell membrane permeability of various middle molecules with potent bioactivities is efficiently studied using molecular dynamics simulations. Insight of this behavior is thoroughly investigated using FMO-QM calculations. Results obtained in the present study indicate that non-bonding intramolecular interactions such as hydrogen-bonding and -stacking along with the conformational flexibility of MMs are essential for amicable membrane permeation. These results are interesting and are nice example for this theoretical calculation approach that could be used to study the permeability of other middle molecules. This work was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number 18ae0101047.

Keywords: fragment molecular orbital theory, membrane permeability, middle molecules, molecular dynamics simulation

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Authors: Sadaf Ilyas, Saba Riaz

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The extensive use of antibiotics has led to increases emergence of antibiotic-resistant organisms. Pseudomonas is a notorious opportunistic pathogen involoved in nosocomial infections and exhibit innate resistance to many antibiotics. The present study was conducted to assess the prevalence, levels of antimicrobial susceptibility and resistance mechanisms of Pseudomonas. A total of thirty clinical strains of Pseudomonas were isolated from different clinical sites of infection. All clinical specimens were collected from Chughtais Lahore Lab. Jail road, during 8-07-2010 to 11-01-2011. Biochemical characterization was done using routine biochemical tests. Antimicrobial susceptibility was determined by Kirby-Baeur method. The plasmids were isolated from all the strains and digested with restriction enzyme PstI and EcoRI. Transfer of Multi-resistance plasmid was checked via transformation and conjugation to confirm the plasmid mediated resistance to antibiotics. The prevalence of Pseudomonas in clinical specimens was found out to be 14% of all bacterial infections. IPM has shown to be the most effective drug against Pseudomonas followed by CES, PTB and meropenem, wheareas most of the Pseudomonas strains have developed significant resistance against Penicillins and some Cephalasporins. Antibiotic resistance determinants were carried by plasmids, as they conferred resistance to transformed K1 strains. The isolates readily undergo conjugation, transferring the resistant genes to other strains, illustrating the high rates of cross infection and nosocomial infection in the immunocompromised patients.

Keywords: pseudomonas, antibiotics, drug resistance, horizontal gene transfer

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Authors: Jeffrey Tzu-Hao Tsai, Yi-Shan Wong

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This article proposes a cohort-age-period (CAP) model to characterize multi-population mortality processes using cohort, age, and period variables. Distinct from the factor-based Lee-Carter-type decomposition mortality model, this approach is empirically based and includes the age, period, and cohort variables into the equation system. The model not only provides a fruitful intuition for explaining multivariate mortality change rates but also has a better performance in forecasting future patterns. Using the US and the UK mortality data and performing ten-year out-of-sample tests, our approach shows smaller mean square errors in both countries compared to the models in the literature.

Keywords: longevity risk, stochastic mortality model, multivariate mortality rate, risk management

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