BACKGROUND Incidence of cholangiocarcinoma(CCA)is rising,with overall prognosis remaining very poor.Reasons for the high mortality of CCA include its late presentation in most patients,when curative options are no lon...BACKGROUND Incidence of cholangiocarcinoma(CCA)is rising,with overall prognosis remaining very poor.Reasons for the high mortality of CCA include its late presentation in most patients,when curative options are no longer feasible,and poor response to systemic therapies for advanced disease.Late presentation presents a large barrier to improving outcomes and is often associated with diagnosis via mergency presentation(EP).Earlier diagnoses may be made by Two Week Wait(TWW)referrals through General practitioner(GP).We hypothesise that TWW referrals and EP routes to diagnosis differ across regions in England.AIM To investigate routes to diagnosis of CCA over time,regional variation and influencing factors.METHODS We linked patient records from the National Cancer Registration Dataset to Hospital Episode Statistics,Cancer Waiting Times and Cancer Screening Programme datasets to define routes to diagnosis and certain patient characteristics for patients diagnosed 2006-2017 in England.We used linear probability models to investigate geographic variation by assessing the proportions of patients diagnosed via TWW referral or EP across Cancer Alliances in England,adjusting for potential confounders.Correlation between the proportion of people diagnosed by TWW referral and EP was investigated with Spearman’s correlation coefficient.RESULTS Of 23632 patients diagnosed between 2006-2017 in England,the most common route to diagnosis was EP(49.6%).Non-TWW GP referrals accounted for 20.5%of diagnosis routes,13.8%were diagnosed by TWW referral,and the remainder 16.2%were diagnosed via an‘other’or Unknown route.The proportion diagnosed via a TWW referral doubled between 2006-2017 rising from 9.9%to 19.8%,conversely EP diagnosis route declined,falling from 51.3%to 46.0%.Statistically significant variation in both the TWW referral and EP proportions was found across Cancer Alliances.Age,presence of comorbidity and underlying liver disease were independently associated with both a lower proportion of patients diagnosed via TWW referral,and a higher proportion diagnosed by EP after adjusting for other potential confounders.CONCLUSION There is significant geographic and socio-demographic variation in routes to diagnosis of CCA in England.Knowledge sharing of best practice may improve diagnostic pathways and reduce unwarranted variation.展开更多
In this paper we employ artificial neural networks for predictive approximation of generalized functions having crucial applications in different areas of science including mechanical and chemical engineering, signal ...In this paper we employ artificial neural networks for predictive approximation of generalized functions having crucial applications in different areas of science including mechanical and chemical engineering, signal processing, information transfer, telecommunications, finance, etc. Results of numerical analysis are discussed. It is shown that the known Gibb’s phenomenon does not occur.展开更多
Iris recognition technology(IRT)-based authentication is a biometric financial technology(FinTech)application used to automate user recognition and verification.In addition to being a controversial technology with var...Iris recognition technology(IRT)-based authentication is a biometric financial technology(FinTech)application used to automate user recognition and verification.In addition to being a controversial technology with various facilitators and inhibitors,the adoption of IRT-based FinTech is driven by contextual factors,such as customer perceptions,deployed biometric technology,and financial transaction settings.Due to its controversial and contextual properties,analyzing IRT-based FinTech acceptance is challenging.This study uses a net valence framework to investigate the salient positive and negative factors influencing the intention to use IRT-based FinTech in automated teller machines(ATMs)in Jordan.This study is pertinent because there is a dearth of research on IRT-based FinTech in the relevant literature;most previous research has taken purely engineering and technical approaches.Furthermore,despite considerable investments by banks and other financial institutions in this FinTech,target user adoption is minimal,and only 6% of Jordan’s ATM transactions are currently IRT-enabled.This study employs mixed methods.In the first qualitative study,17 Jordanian customers were interviewed regarding the benefits and risks of IRT-based FinTech in ATMs.Content analyses determined the most important concepts or themes.The advantages include financial security,convenience,and FinTech-enabled hygiene,whereas the concerns include performance,financial,privacy,and physical risks.The research model is constructed based on the qualitative study and theoretical underpinnings,wherein 631 Jordanian bank customers with active ATM accounts were surveyed to validate the research model.The findings indicate that IRT-based FinTech usage in ATMs is proportional to its perceived value.In descending order of effect,financial security,FinTech-enabled hygiene,and convenience benefits positively impact perceived value.Privacy,financial,and physical risks have negative impacts on perceived value,whereas performance risk has no effect.This study contributes to the relatively untapped domain of biometric technology in information systems,with important theoretical and practical implications.展开更多
BACKGROUND Mixed neuroendocrine non-neuroendocrine neoplasm(MiNEN)is a rare diagnosis,mainly encountered in the gastro-entero-pancreatic tract.There is limited knowledge of its epidemiology,prognosis and biology,and t...BACKGROUND Mixed neuroendocrine non-neuroendocrine neoplasm(MiNEN)is a rare diagnosis,mainly encountered in the gastro-entero-pancreatic tract.There is limited knowledge of its epidemiology,prognosis and biology,and the best management for affected patients is still to be defined.AIM To investigate clinical-pathological characteristics,treatment modalities and survival outcomes of a retrospective cohort of patients with a diagnosis of MiNEN.METHODS Consecutive patients with a histologically proven diagnosis of MiNEN were identified at 5 European centres.Patient data were retrospectively collected from medical records.Pathological samples were reviewed to ascertain compliance with the 2017 World Health Organisation definition of MiNEN.Tumour responses to systemic treatment were assessed according to the Response Evaluation Criteria in Solid Tumours 1.1.Kaplan-Meier analysis was applied to estimate survival outcomes.Associations between clinical-pathological characteristics and survival outcomes were explored using Log-rank test for equality of survivors functions(univariate)and Cox-regression analysis(multivariable).RESULTS Sixty-nine consecutive patients identified;Median age at diagnosis:64 years.Males:63.8%.Localised disease(curable):53.6%.Commonest sites of origin:colon-rectum(43.5%)and oesophagus/oesophagogastric junction(15.9%).The neuroendocrine component was;predominant in 58.6%,poorly differentiated in 86.3%,and large cell in 81.25%,of cases analysed.Most distant metastases analysed(73.4%)were occupied only by a poorly differentiated neuroendocrine component.Ninety-four percent of patients with localised disease underwent curative surgery;53%also received perioperative treatment,most often in line with protocols for adenocarcinomas from the same sites of origin.Chemotherapy was offered to most patients(68.1%)with advanced disease,and followed protocols for pure neuroendocrine carcinomas or adenocarcinomas in equal proportion.In localised cases,median recurrence free survival(RFS);14.0 months(95%CI:9.2-24.4),and median overall survival(OS):28.6 months(95%CI:18.3-41.1).On univariate analysis,receipt of perioperative treatment(vs surgery alone)did not improve RFS(P=0.375),or OS(P=0.240).In advanced cases,median progression free survival(PFS);5.6 months(95%CI:4.4-7.4),and median OS;9.0 months(95%CI:5.2-13.4).On univariate analysis,receipt of palliative active treatment(vs best supportive care)prolonged PFS and OS(both,P<0.001).CONCLUSION MiNEN is most commonly driven by a poorly differentiated neuroendocrine component,and has poor prognosis.Advances in its biological understanding are needed to identify effective treatments and improve patient outcomes.展开更多
Machine Learning becomes a part of our life in recent days and everything we do in interlinked with machine learning. As a technocrat, we tried to implement machine learning with Internet of Things (IoT) for better im...Machine Learning becomes a part of our life in recent days and everything we do in interlinked with machine learning. As a technocrat, we tried to implement machine learning with Internet of Things (IoT) for better implementation of technology in organizations for security. We designed an sample architecture which will carry the burden of safeguarding the organizational data with IoT using machine learning with an effective manner and in this case we were proposing utilization of cloud computing for better understanding of data storage and retrieval process. Machine learning is used for the prediction models based on which we need to perform high level analysis of data and using IoT we promote authorization mechanism based on which we recognize the appropriate recipient of data and cloud for managing the data services with the three-tier architecture. We present the architecture we are proposing for better utilization of machine learning and IoT with cloud architecture.展开更多
Synthetic and naturally occurring particles,such as nanoparticles(NPs)and exosomes;a type of extracellular vesicles(EVs),have garnered widespread attention across various fields,including biomaterials,oncology,and del...Synthetic and naturally occurring particles,such as nanoparticles(NPs)and exosomes;a type of extracellular vesicles(EVs),have garnered widespread attention across various fields,including biomaterials,oncology,and delivery systems for drugs and vaccines.Traditional methods for identifying NPs and EVs,such as transmission electron microscopy,are often prohibitively expensive and labor-intensive.As an alternative,the assessment of electrokinetic attributes such as zeta potential or electrophoretic mobility,conductance,and mean count rate,offers a more cost-effective,rapid,and reliable means of characterizing these particles.In this context,we introduce the first application of a quantum machine learning(QML)-based electrokinetic mining for the identification of green-synthesized iron-and cobalt-based NPs,as well as exosomes derived from human embryonic stem cells(hESC),human lung cancer(A549)cells,and colorectal cancer(CRC)cells,based solely on their electrokinetic attributes.Comparative analyses involving cross-validation,train-test splits,confusion matrices,and Receiver Operating Characteristic(ROC)curves revealed that classical ML techniques could accurately identify the types of NPs and EVs.Notably,QML demonstrated proficiency in differentiating between various NPs and EVs,including the distinction of EVs in the plasma of CRC patients versus those of healthy individuals.Furthermore,QML’s application has been extended to the identification of NPs along with EVs in the plasma of CRC patients and experimental mice,achieving higher prediction performance even with a minimal training dataset,demonstrating that QML based electrokinetic mining could identify NPs or EVs with minimal training data,thereby facilitating novel clinical development in the realm of liquid biopsies.展开更多
Conflicts between supply chain members emerge because individual strategic actions may not be jointly optimal.Efforts to forecast consumer demand represent a source of conflict.The coordination of forecasts requires a...Conflicts between supply chain members emerge because individual strategic actions may not be jointly optimal.Efforts to forecast consumer demand represent a source of conflict.The coordination of forecasts requires a powerful incentive alignment approach.This work proposes a smart contract equipped consortium blockchain system that creates an incentive structure that makes coordination with respect to forecasts economically appealing.Distortions of demand information due to uncoordinated forecasting are captured by a bullwhip measure that factors both forecast error and variance.Cooperation under the system is shown to help minimize this bullwhip measure,thus generating new outcomes for the participants that allow for a higher reward.Under a fixed payout structure,the system achieves credibility of continued cooperation,thus promoting an optimally coordinated equilibrium between the retailer and supplier.Blockchain technology represents a novel information system and consensus formation mechanism that can intermediate the behavior of a supply chain network.展开更多
Maritime shipping is considered the most efficient,low-cost means for transporting large quantities of freight over significant distances.However,this process also causes negative environmental and societal impacts.Th...Maritime shipping is considered the most efficient,low-cost means for transporting large quantities of freight over significant distances.However,this process also causes negative environmental and societal impacts.Therefore,environmental sustainability is a pressing issue for maritime shipping management,given the interest in addressing important issues that affect the safety,security,and air and water quality as part of the efficient movement of freight throughout the coasts and waterways and associated port facilities worldwide.In丒depth studies of maritime transportation systems(MTS)can be used to identify key environmental impact indicators within the transportation system.This paper develops a tool for decision making in complex environments;this tool will quantify and rank preferred environmental impact indicators within a MTS.Such a model will help decision-makers to achieve the goals of improved environmental sustainability.The model will also provide environmental policy丒 makers in the shipping industry with an analytical tool that can evaluate tradeoffs within the system and identify possible alternatives to mitigate detrimental effects on the environment.展开更多
Blockchain is gaining massive attention and has the potential to impact different types of record-keeping processes.It is one of the most innovative technologies potential enough to impact every industry from financia...Blockchain is gaining massive attention and has the potential to impact different types of record-keeping processes.It is one of the most innovative technologies potential enough to impact every industry from financial to educational institutes.Recently,consensus mechanisms have enabled distributed ledger technologies(DLTs)to find their applications and values in various sectors.A consensus algorithm is an essential element of blockchain networks.Consensus mechanisms function to ensure the transaction's validity,reliability,and authenticity in a peer-to-peer network.The consensus algorithm assures the authenticity of transactions in a trustless and distributed manner.Choosing the right consensus algorithm plays a crucial role in the performance of a blockchain application.In this paper,a detailed survey of different types of blockchain consensus algorithms that are popular and commonly used today is presented.展开更多
文摘BACKGROUND Incidence of cholangiocarcinoma(CCA)is rising,with overall prognosis remaining very poor.Reasons for the high mortality of CCA include its late presentation in most patients,when curative options are no longer feasible,and poor response to systemic therapies for advanced disease.Late presentation presents a large barrier to improving outcomes and is often associated with diagnosis via mergency presentation(EP).Earlier diagnoses may be made by Two Week Wait(TWW)referrals through General practitioner(GP).We hypothesise that TWW referrals and EP routes to diagnosis differ across regions in England.AIM To investigate routes to diagnosis of CCA over time,regional variation and influencing factors.METHODS We linked patient records from the National Cancer Registration Dataset to Hospital Episode Statistics,Cancer Waiting Times and Cancer Screening Programme datasets to define routes to diagnosis and certain patient characteristics for patients diagnosed 2006-2017 in England.We used linear probability models to investigate geographic variation by assessing the proportions of patients diagnosed via TWW referral or EP across Cancer Alliances in England,adjusting for potential confounders.Correlation between the proportion of people diagnosed by TWW referral and EP was investigated with Spearman’s correlation coefficient.RESULTS Of 23632 patients diagnosed between 2006-2017 in England,the most common route to diagnosis was EP(49.6%).Non-TWW GP referrals accounted for 20.5%of diagnosis routes,13.8%were diagnosed by TWW referral,and the remainder 16.2%were diagnosed via an‘other’or Unknown route.The proportion diagnosed via a TWW referral doubled between 2006-2017 rising from 9.9%to 19.8%,conversely EP diagnosis route declined,falling from 51.3%to 46.0%.Statistically significant variation in both the TWW referral and EP proportions was found across Cancer Alliances.Age,presence of comorbidity and underlying liver disease were independently associated with both a lower proportion of patients diagnosed via TWW referral,and a higher proportion diagnosed by EP after adjusting for other potential confounders.CONCLUSION There is significant geographic and socio-demographic variation in routes to diagnosis of CCA in England.Knowledge sharing of best practice may improve diagnostic pathways and reduce unwarranted variation.
文摘In this paper we employ artificial neural networks for predictive approximation of generalized functions having crucial applications in different areas of science including mechanical and chemical engineering, signal processing, information transfer, telecommunications, finance, etc. Results of numerical analysis are discussed. It is shown that the known Gibb’s phenomenon does not occur.
文摘Iris recognition technology(IRT)-based authentication is a biometric financial technology(FinTech)application used to automate user recognition and verification.In addition to being a controversial technology with various facilitators and inhibitors,the adoption of IRT-based FinTech is driven by contextual factors,such as customer perceptions,deployed biometric technology,and financial transaction settings.Due to its controversial and contextual properties,analyzing IRT-based FinTech acceptance is challenging.This study uses a net valence framework to investigate the salient positive and negative factors influencing the intention to use IRT-based FinTech in automated teller machines(ATMs)in Jordan.This study is pertinent because there is a dearth of research on IRT-based FinTech in the relevant literature;most previous research has taken purely engineering and technical approaches.Furthermore,despite considerable investments by banks and other financial institutions in this FinTech,target user adoption is minimal,and only 6% of Jordan’s ATM transactions are currently IRT-enabled.This study employs mixed methods.In the first qualitative study,17 Jordanian customers were interviewed regarding the benefits and risks of IRT-based FinTech in ATMs.Content analyses determined the most important concepts or themes.The advantages include financial security,convenience,and FinTech-enabled hygiene,whereas the concerns include performance,financial,privacy,and physical risks.The research model is constructed based on the qualitative study and theoretical underpinnings,wherein 631 Jordanian bank customers with active ATM accounts were surveyed to validate the research model.The findings indicate that IRT-based FinTech usage in ATMs is proportional to its perceived value.In descending order of effect,financial security,FinTech-enabled hygiene,and convenience benefits positively impact perceived value.Privacy,financial,and physical risks have negative impacts on perceived value,whereas performance risk has no effect.This study contributes to the relatively untapped domain of biometric technology in information systems,with important theoretical and practical implications.
文摘BACKGROUND Mixed neuroendocrine non-neuroendocrine neoplasm(MiNEN)is a rare diagnosis,mainly encountered in the gastro-entero-pancreatic tract.There is limited knowledge of its epidemiology,prognosis and biology,and the best management for affected patients is still to be defined.AIM To investigate clinical-pathological characteristics,treatment modalities and survival outcomes of a retrospective cohort of patients with a diagnosis of MiNEN.METHODS Consecutive patients with a histologically proven diagnosis of MiNEN were identified at 5 European centres.Patient data were retrospectively collected from medical records.Pathological samples were reviewed to ascertain compliance with the 2017 World Health Organisation definition of MiNEN.Tumour responses to systemic treatment were assessed according to the Response Evaluation Criteria in Solid Tumours 1.1.Kaplan-Meier analysis was applied to estimate survival outcomes.Associations between clinical-pathological characteristics and survival outcomes were explored using Log-rank test for equality of survivors functions(univariate)and Cox-regression analysis(multivariable).RESULTS Sixty-nine consecutive patients identified;Median age at diagnosis:64 years.Males:63.8%.Localised disease(curable):53.6%.Commonest sites of origin:colon-rectum(43.5%)and oesophagus/oesophagogastric junction(15.9%).The neuroendocrine component was;predominant in 58.6%,poorly differentiated in 86.3%,and large cell in 81.25%,of cases analysed.Most distant metastases analysed(73.4%)were occupied only by a poorly differentiated neuroendocrine component.Ninety-four percent of patients with localised disease underwent curative surgery;53%also received perioperative treatment,most often in line with protocols for adenocarcinomas from the same sites of origin.Chemotherapy was offered to most patients(68.1%)with advanced disease,and followed protocols for pure neuroendocrine carcinomas or adenocarcinomas in equal proportion.In localised cases,median recurrence free survival(RFS);14.0 months(95%CI:9.2-24.4),and median overall survival(OS):28.6 months(95%CI:18.3-41.1).On univariate analysis,receipt of perioperative treatment(vs surgery alone)did not improve RFS(P=0.375),or OS(P=0.240).In advanced cases,median progression free survival(PFS);5.6 months(95%CI:4.4-7.4),and median OS;9.0 months(95%CI:5.2-13.4).On univariate analysis,receipt of palliative active treatment(vs best supportive care)prolonged PFS and OS(both,P<0.001).CONCLUSION MiNEN is most commonly driven by a poorly differentiated neuroendocrine component,and has poor prognosis.Advances in its biological understanding are needed to identify effective treatments and improve patient outcomes.
文摘Machine Learning becomes a part of our life in recent days and everything we do in interlinked with machine learning. As a technocrat, we tried to implement machine learning with Internet of Things (IoT) for better implementation of technology in organizations for security. We designed an sample architecture which will carry the burden of safeguarding the organizational data with IoT using machine learning with an effective manner and in this case we were proposing utilization of cloud computing for better understanding of data storage and retrieval process. Machine learning is used for the prediction models based on which we need to perform high level analysis of data and using IoT we promote authorization mechanism based on which we recognize the appropriate recipient of data and cloud for managing the data services with the three-tier architecture. We present the architecture we are proposing for better utilization of machine learning and IoT with cloud architecture.
基金supported by the National Cancer Institute(NCI)R00 CA226353-01A1,Cancer Research Foundation Young Investigator Award and a Lung Cancer Research Foundation(LCRF)Pilot Project Award to HJC.
文摘Synthetic and naturally occurring particles,such as nanoparticles(NPs)and exosomes;a type of extracellular vesicles(EVs),have garnered widespread attention across various fields,including biomaterials,oncology,and delivery systems for drugs and vaccines.Traditional methods for identifying NPs and EVs,such as transmission electron microscopy,are often prohibitively expensive and labor-intensive.As an alternative,the assessment of electrokinetic attributes such as zeta potential or electrophoretic mobility,conductance,and mean count rate,offers a more cost-effective,rapid,and reliable means of characterizing these particles.In this context,we introduce the first application of a quantum machine learning(QML)-based electrokinetic mining for the identification of green-synthesized iron-and cobalt-based NPs,as well as exosomes derived from human embryonic stem cells(hESC),human lung cancer(A549)cells,and colorectal cancer(CRC)cells,based solely on their electrokinetic attributes.Comparative analyses involving cross-validation,train-test splits,confusion matrices,and Receiver Operating Characteristic(ROC)curves revealed that classical ML techniques could accurately identify the types of NPs and EVs.Notably,QML demonstrated proficiency in differentiating between various NPs and EVs,including the distinction of EVs in the plasma of CRC patients versus those of healthy individuals.Furthermore,QML’s application has been extended to the identification of NPs along with EVs in the plasma of CRC patients and experimental mice,achieving higher prediction performance even with a minimal training dataset,demonstrating that QML based electrokinetic mining could identify NPs or EVs with minimal training data,thereby facilitating novel clinical development in the realm of liquid biopsies.
文摘Conflicts between supply chain members emerge because individual strategic actions may not be jointly optimal.Efforts to forecast consumer demand represent a source of conflict.The coordination of forecasts requires a powerful incentive alignment approach.This work proposes a smart contract equipped consortium blockchain system that creates an incentive structure that makes coordination with respect to forecasts economically appealing.Distortions of demand information due to uncoordinated forecasting are captured by a bullwhip measure that factors both forecast error and variance.Cooperation under the system is shown to help minimize this bullwhip measure,thus generating new outcomes for the participants that allow for a higher reward.Under a fixed payout structure,the system achieves credibility of continued cooperation,thus promoting an optimally coordinated equilibrium between the retailer and supplier.Blockchain technology represents a novel information system and consensus formation mechanism that can intermediate the behavior of a supply chain network.
文摘Maritime shipping is considered the most efficient,low-cost means for transporting large quantities of freight over significant distances.However,this process also causes negative environmental and societal impacts.Therefore,environmental sustainability is a pressing issue for maritime shipping management,given the interest in addressing important issues that affect the safety,security,and air and water quality as part of the efficient movement of freight throughout the coasts and waterways and associated port facilities worldwide.In丒depth studies of maritime transportation systems(MTS)can be used to identify key environmental impact indicators within the transportation system.This paper develops a tool for decision making in complex environments;this tool will quantify and rank preferred environmental impact indicators within a MTS.Such a model will help decision-makers to achieve the goals of improved environmental sustainability.The model will also provide environmental policy丒 makers in the shipping industry with an analytical tool that can evaluate tradeoffs within the system and identify possible alternatives to mitigate detrimental effects on the environment.
文摘Blockchain is gaining massive attention and has the potential to impact different types of record-keeping processes.It is one of the most innovative technologies potential enough to impact every industry from financial to educational institutes.Recently,consensus mechanisms have enabled distributed ledger technologies(DLTs)to find their applications and values in various sectors.A consensus algorithm is an essential element of blockchain networks.Consensus mechanisms function to ensure the transaction's validity,reliability,and authenticity in a peer-to-peer network.The consensus algorithm assures the authenticity of transactions in a trustless and distributed manner.Choosing the right consensus algorithm plays a crucial role in the performance of a blockchain application.In this paper,a detailed survey of different types of blockchain consensus algorithms that are popular and commonly used today is presented.
