Early proactive monitoring of DNA-thioguanine in patients with Crohn’s disease predicts thiopurine-induced late leucopenia in NUDT15/TPMT normal metabolizers

BACKGROUND Thiopurine-induced leucopenia significantly hinders the wide application of thiopurines.Dose optimization guided by nudix hydrolase 15(NUDT15)has significantly reduced the early leucopenia rate,but there are no definitive biomarkers for late risk leucopenia prediction.AIM To determine the predictive value of early monitoring of DNA-thioguanine(DNATG)or 6-thioguanine nucleotides(6TGN)for late leucopenia under a NUDT15-guided thiopurine dosing strategy in patients with Crohn’s disease(CD).METHODS Blood samples were collected within two months after thiopurine initiation for detection of metabolite concentrations.Late leucopenia was defined as a leukocyte count<3.5×10^(9)/L over two months.RESULTS Of 148 patients studied,late leucopenia was observed in 15.6%(17/109)of NUDT15/thiopurine methyltransferase(TPMT)normal and 64.1%(25/39)of intermediate metabolizers.In patients suffering late leucopenia,early DNATG levels were significantly higher than in those who did not develop late leucopenia(P=4.9×10^(-13)).The DNATG threshold of 319.43 fmol/μg DNA could predict late leucopenia in the entire sample with an area under the curve(AUC)of 0.855(sensitivity 83%,specificity 81%),and in NUDT15/TPMT normal metabolizers,the predictive performance of a threshold of 315.72 fmol/μg DNA was much more remarkable with an AUC of 0.902(sensitivity 88%,specificity 85%).6TGN had a relatively poor correlation with late leucopenia whether in the entire sample(P=0.021)or NUDT15/TPMT normal or intermediate metabolizers(P=0.018,P=0.55,respectively).CONCLUSION Proactive therapeutic drug monitoring of DNATG could be an effective strategy to prevent late leucopenia in both NUDT15/TPMT normal and intermediate metabolizers with CD,especially the former.

Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises

As cyber threats keep changing and business environments adapt, a comprehensive approach to disaster recovery involves more than just defensive measures. This research delves deep into the strategies required to respond to threats and anticipate and mitigate them proactively. Beginning with understanding the critical need for a layered defense and the intricacies of the attacker’s journey, the research offers insights into specialized defense techniques, emphasizing the importance of timely and strategic responses during incidents. Risk management is brought to the forefront, underscoring businesses’ need to adopt mature risk assessment practices and understand the potential risk impact areas. Additionally, the value of threat intelligence is explored, shedding light on the importance of active engagement within sharing communities and the vigilant observation of adversary motivations. “Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises” is a comprehensive guide for organizations aiming to fortify their cybersecurity posture, marrying best practices in proactive and reactive measures in the ever-challenging digital realm.

The computerized LASSI-BC Test versus the Standard LASSI-L Paper-and-Pencil Version in Community-Based-Samples

Proactive Semantic Interference (PSI) and failure to recover from PSI (frPSI), are novel constructs assessed by the LASSI-L. These measures are sensitive to cognitive changes in early Mild Cognitive Impairment (MCI) and preclinical AD determined by Aβ load using PET. The goal of this study was to compare a new computerized version of the LASSI-L (LASSI-Brief Computerized) to the standard paper-and-pencil version of the test. In this study, we examined 110 cognitively unimpaired (CU) older adults and 79 with amnestic MCI (aMCI) who were administered the paper-and-pencil form of the LASSI-L. Their performance was compared with 62 CU older adults and 52 aMCI participants examined using the LASSI-BC. After adjustment for covariates (degree of initial learning, sex, education, and language of evaluation) both the standard and computerized versions distinguished between aMCI and CU participants. The performance of CU and aMCI groups using either form was relatively commensurate. Importantly, an optimal combination of Cued B2 recall and Cued B1 intrusions on the LASSI-BC yielded an area under the ROC curve of .927, a sensitivity of 92.3% and specificity of 88.1%, relative to an area under the ROC curve of .815, a sensitivity of 72.5%, and a specificity of 79.1% obtained for the paper-and-pencil LASSI-L. Overall, the LASSI-BC was comparable, and in some ways, superior to the paper-and-pencil LASSI-L. Advantages of the LASSI-BC include a more standardized administration, suitability for remote assessment, and an automated scoring mechanism that can be verified by a built-in audio recording of responses.

Certis: Cloud Asset Management & Threat Evaluation Using Behavioral Fingerprinting at Application Layer

This paper introduces Certis, a powerful framework that addresses the challenges of cloud asset tracking, management, and threat detection in modern cybersecurity landscapes. It enhances asset identification and anomaly detection through SSL certificate parsing, cloud service provider integration, and advanced fingerprinting techniques like JARM at the application layer. Current work will focus on cross-layer malicious behavior identification to further enhance its capabilities, including minimizing false positives through AI-based learning techniques. Certis promises to offer a powerful solution for organizations seeking proactive cybersecurity defenses in the face of evolving threats.

China’s Proactive Fiscal Policy

In contrast to the traditional Western approach to macro-fiscal management,China’s proactive fiscal policy is founded on a people-centered development philosophy and,with distinctive Chinese characteristics,is a significant policy innovation of macroeconomic management in the Chinese modernization.Although there are notable distinctions between the Western“Keynesian”and the“nonKeynesian”schools of thought,both of these approaches’core policy goals and methodological roots are the same,composing the traditional Western macro-fiscal approach.This approach faces increasing real dilemmas.China’s proactive fiscal policy,however,places greater emphasis on future potential growth rates in addition to equilibrium between supply and demand,achieving a fiscal policy transformation with a new approach.In this paper we argue that with such a new approach,China should reconsider the nature and reasonable level of the fiscal deficit,the function and risk assessment criteria of government debt,the scope and effects of reductions in taxes and fees,its approach and focus of demand management,and the costs and resulting efficiencies of policies in order to develop a new fiscal policy paradigm that is more in line with its stated goals.

How Do Mind-Body Practices Benefit Employees? A Daily Diary Study of Mind–Body Practices after Work and Employees’ Next-Day Proactive Behavior

Although it is becoming increasingly popular for organizations to offer programs of mind–body practices to their employees to improve their physical and mental health,the effects that after-work sessions of mind–body prac-tices have on employees’work behavior remain unclear.Using the model of proactive motivation and experience sampling,this study explored the relationship between employees’mind–body practices after work and their proactive behavior in the workplace on the following day.A multilevel path analysis of data from 82 employees over seven consecutive workdays showed that employees’mind–body practices after work had a positive effect on their proactive behavior in the workplace on the following day.The relationship was mediated by next-day high-activated positive affect and problem-solving confidence.Furthermore,job control positively moderated the rela-tionship between high-activated positive affect and proactive behavior but not that between problem-solving con-fidence and proactive behavior.We discuss the theoretical and practical implications of thesefindings,and propose future research directions.

A novel proactive soft load balancing framework for ultra dense network

A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.

The Impact of Self-Efficacy and Work Engagement on Healthcare Professionals’ Proactive Behavior

Job crafting (JC) is a form of proactive behavior and refers to the initiatives employees that could take to change their tasks or other job characteristics to achieve the best person-job fit. JC consists of six dimensions: seeking structural and social job resources, as well as challenges, hindering job demands, optimizing job demands, and delegating tasks. The aim of the present study was to explore the impact of self-efficacy and work engagement on healthcare professionals’ (HP) proactive behavior. A convenience sample of 295 HP working in Primary and Secondary healthcare structures of Northern Greece completed a questionnaire that included: 1) demographic/occupational characteristics, 2) the Job Crafting Scale, 3) the Generalized Self-Efficacy Scale (GSE) and 4) the Utrecht Work Engagement Scale (UWES). Increased age was found to be associated with decreased levels of seeking social job resources (p < 0.01). Education level was positively associated with increased levels of seeking structural job resources (p < 0.01), seeking challenges (p < 0.05), and optimizing job demands (p < 0.05), while job position was found to be negatively related to delegating tasks (p < 0.01). Self-efficacy was positively associated with increased levels of seeking structural resources (p < 0.001), challenges (p < 0.001), and increased levels of optimizing job demands (p < 0.001), while it was positively associated with decreased levels of delegating tasks (p < 0.05). In addition, increased work engagement was found to be associated with increased levels of seeking social job resources (p < 0.05), challenges (p < 0.01), and optimizing job demands (p < 0.01). Findings highlight the importance of self-efficacy, work engagement and individual characteristics in the realization of a resourceful work environment and HP’ adjustment in the organization. Thus, interventions that promote HP’ JC proactive behaviors should be encouraged.

A Novel Computerized Cognitive Test for the Detection of Mild Cognitive Impairment and Its Association with Neurodegeneration in Alzheimer’s Disease Prone Brain Regions

During the prodromal stage of Alzheimer’s disease (AD), neurodegenerative changes can be identified by measuring volumetric loss in AD-prone brain regions on MRI. Cognitive assessments that are sensitive enough to measure the early brain-behavior manifestations of AD and that correlate with biomarkers of neurodegeneration are needed to identify and monitor individuals at risk for dementia. Weak sensitivity to early cognitive change has been a major limitation of traditional cognitive assessments. In this study, we focused on expanding our previous work by determining whether a digitized cognitive stress test, the Loewenstein-Acevedo Scales for Semantic Interference and Learning, Brief Computerized Version (LASSI-BC) could differentiate between Cognitively Unimpaired (CU) and amnestic Mild Cognitive Impairment (aMCI) groups. A second focus was to correlate LASSI-BC performance to volumetric reductions in AD-prone brain regions. Data was gathered from 111 older adults who were comprehensively evaluated and administered the LASSI-BC. Eighty-seven of these participants (51 CU;36 aMCI) underwent MR imaging. The volumes of 12 AD-prone brain regions were related to LASSI-BC and other memory tests correcting for False Discovery Rate (FDR). Results indicated that, even after adjusting for initial learning ability, the failure to recover from proactive semantic interference (frPSI) on the LASSI-BC differentiated between CU and aMCI groups. An optimal combination of frPSI and initial learning strength on the LASSI-BC yielded an area under the ROC curve of 0.876 (76.1% sensitivity, 82.7% specificity). Further, frPSI on the LASSI-BC was associated with volumetric reductions in the hippocampus, amygdala, inferior temporal lobes, precuneus, and posterior cingulate.

An efficient proactive RSA scheme for large-scale ad hoc networks

A previous proactive RSA scheme for large-scale ad hoc network has been shown to be faulty. In this paper, we present a new proactive RSA scheme for ad hoc networks, which includes four protocols： the initial key distribution protocol, the share refreshing protocol, the share distribution protocol, and the signature generation protocol. This scheme has two advantages： the building blocks are secure, and the system is efficient.

Proactive Spectrum Monitoring for Suspicious Wireless Powered Communications in Dynamic Spectrum Sharing Networks

This paper studies the proactive spec-trum monitoring with one half-duplex spectrum moni-tor(SM)to cope with the potential suspicious wireless powered communications(SWPC)in dynamic spec-trum sharing networks.The jamming-assisted spec-trum monitoring scheme via spectrum monitoring data(SMD)transmission is proposed to maximize the sum ergodic monitoring rate at SM.In SWPC,the suspi-cious communications of each data block occupy mul-tiple independent blocks,with a block dedicated to the wireless energy transfer by the energy-constrained suspicious nodes with locations in a same cluster(symmetric scene)or randomly distributed(asymmet-ric scene)and the remaining blocks used for the in-formation transmission from suspicious transmitters(STs)to suspicious destination(SD).For the sym-metric scene,with a given number of blocks for SMD transmission,namely the jamming operation,we first reveal that SM should transmit SMD signal(jam the SD)with tolerable maximum power in the given blocks.The perceived suspicious signal power at SM could be maximized,and thus so does the correspond-ing sum ergodic monitoring rate.Then,we further reveal one fundamental trade-off in deciding the op-timal number of given blocks for SMD transmission.For the asymmetric scene,a low-complexity greedy block selection scheme is proposed to guarantee the optimal performance.Simulation results show that the jamming-assisted spectrum monitoring schemes via SMD transmission achieve much better perfor-mance than conventional passive spectrum monitor-ing,since the proposed schemes can obtain more accu-rate and effective spectrum characteristic parameters,which provide basic support for fine-grained spectrum management and a solution for spectrum security in dynamic spectrum sharing network.

Data-Driven Model for Risk Assessment of Cable Fire in Utility Tunnels Using Evidential Reasoning Approach

Cable fire is one of the most important events for operation and maintenance(O&M)safety in underground utility tunnels(UUTs).Since there are limited studies about cable fire risk assessment,a comprehensive assessment model is proposed to evaluate the cable fire risk in different UUT sections and improve O&M efficiency.Considering the uncertainties in the risk assessment,an evidential reasoning(ER)approach is used to combine quantitative sensor data and qualitative expert judgments.Meanwhile,a data transformation technique is contributed to transform continuous data into a five-grade distributed assessment.Then,a case study demonstrates how the model and the ER approach are established.The results show that in Shenzhen,China,the cable fire risk in District 8,B Road is the lowest,while more resources should be paid in District 3,C Road and District 25,C Road,which are selected as comparative roads.Based on the model,a data-driven O&M process is proposed to improve the O&M effectiveness,compared with traditional methods.This study contributes an effective ER-based cable fire evaluation model to improve the O&M efficiency of cable fire in UUTs.

Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

Scientific workflows have gained the emerging attention in sophisti-cated large-scale scientific problem-solving environments.The pay-per-use model of cloud,its scalability and dynamic deployment enables it suited for executing scientific workflow applications.Since the cloud is not a utopian environment,failures are inevitable that may result in experiencingfluctuations in the delivered performance.Though a single task failure occurs in workflow based applications,due to its task dependency nature,the reliability of the overall system will be affected drastically.Hence rather than reactive fault-tolerant approaches,proactive measures are vital in scientific workflows.This work puts forth an attempt to con-centrate on the exploration issue of structuring a nature inspired metaheuristics-Intelligent Water Drops Algorithm(IWDA)combined with an efficient machine learning approach-Support Vector Regression(SVR)for task failure prognostica-tion which facilitates proactive fault-tolerance in the scheduling of scientific workflow applications.The failure prediction models in this study have been implemented through SVR-based machine learning approaches and the precision accuracy of prediction is optimized by IWDA and several performance metrics were evaluated on various benchmark workflows.The experimental results prove that the proposed proactive fault-tolerant approach performs better compared with the other existing techniques.

Verifiable Secret Redistribution for Proactive Secret Sharing Schemes

A new scheme to verifiably redistribute a secret from the old to new shareholders without reconstruction of the secret is presented in this paper. The scheme allows redistribution between different access structures and between different threshold schemes. A point worth mentioning is that this verifiable secret redistribution (VSR) scheme can identify dishonest old shareholders during redistribution without any assumption. A certain technique is adopted to verify the correctness of the old shares of the secret. As a result, the scheme is very efficient. It can be applied to proactive secret sharing (PSS) schemes to construct more flexible and practical proactive secret sharing schemes.

Establishment and application of service mapping model for proactive remanufacturing impeller

Since the complex impeller structure and the difficult remanufacturing process may easily cause advance remanufacturing or excessive use,an optimized design method of impeller and service mapping model was presented for its proactive remanufacturing with setting up to explore the best remanufacturing time point in this work.Considering a certain model of long distance pipeline compressor impeller with the Basquin equation and the design method of impeller,the mathematical relationship between the changes of structure and life of the impeller was established.And the service mapping model between the structure and life was set up and simulated by ANSYS software.Thus,the service mapping model was applied to feedback the original design for proactive remanufacturing.In this work,the best proactive remanufacturing time point of impeller was analyzed with the service mapping model,and the structural parameter values could be optimized at this time point.Meanwhile,in the results of this simulation,it proves that the impeller under this optimization performance could satisfy the impeller operating demands.Therefore,comparing with the traditional optimization design method,the remanufacturing optimized design based on the service mapping model is feasible in proactive remanufacturing for sustainable development.

Entrepreneurial Orientation and Innovation Ecosystems in the Industrial Sector, Central Region, Kampala, Uganda: A Review

This review explores entrepreneurial orientation and innovation ecosystems in the industrial sector of the Central Region, Kampala, Uganda, through an analysis of ten scholarly articles. The study contextualizes the research within the regional landscape and establishes a theoretical framework through a focused literature review. Key findings highlight the intersection of entrepreneurial activities and innovation dynamics, emphasizing the region’s unique contributions to the broader field. Discussions on discrepancies and unexplored territories within the articles offer insights into limitations and research gaps. The manuscript concludes by identifying future research avenues, providing a roadmap for ongoing inquiry into the entrepreneurial and innovative dimensions of the Central Region’s industrial sector. This synthesis underscores the importance of cultivating an entrepreneurial mindset and collaborative innovation strategies for sustainable industrial development in the region.

An Improved Logic Diagram of RCM with the Proactive Maintenance

For some repeatedly occurring failure with root cause,the reliability centered maintenance (RCM) can’t deal with them effectively. So,the logic diagram of RCM was improved by combining it with proactive maintenance technology. First,root cause analysis is used to build a key result-cause chain of the repeatedly occur failure. Then,a reasonable link in the chain,which work station is suitable to be monitored and repaired,should be selected. Finally,the corresponding proactive maintenance measure should be adopted to prevent the matter occur on the chain and broken the key result-cause chain,and the repeatedly occur failure is to be prevent at a deeper level or from the root cause. By doing this,a system engineering method comes into being,not only it can determine the needs of preventive maintenance for equipment,but also determine the proactive maintenance needs for equipment. The analysis result of reliability centered maintenance and the analysis result considering proactive maintenance are combined to form a maintenance guideline containing proactive maintenance strategy.

Proactive Weighted Threshold Signature Based on Generalized Chinese Remainder Theorem

This paper proposes a new proactive weighted threshold signature scheme based on Iflene＇s general secret sharing, the generalized Chinese remainder theorem, and the RSA threshold signature, which is itself based on the Chinese reminder theorem. In our scheme, group members are divided into different subgroups, and a positive weight is associated to each subgroup, where all members of the same subgroup have the same weight. The group signature can be generated if and only if the sum of the weights of members involved is greater than or equal to a fixed threshold value. Meanwhile, the private key of the group members and the public key of the group can be updated periodically by performing a simple operation aimed at refreshing the group signature message. This periodical refreshed individual signature message can enhance the security of the proposed weighted threshold signature scheme.

Service-aware proactive vertical handoff algorithm based on bandwidth requirement prediction

Due to the heterogeneity and versatility of emerging services and applications in wireless networks,it has been a great challenge to improve the system performance with both the awareness of service characteristics and the balance of the traffic between adjacent networks.This paper is committed to solve this problem by introducing a Service-aware Proactive Vertical Handoff(SPVH) algorithm in Heterogeneous Wireless Networks(HWN).A Bandwidth Requirement Prediction Model(BRPM) is illustrated at first,which is adaptive to the system condition variants to forecast traffic requests.Moreover,by adopting a service-aware objective utility function,each user can optimize the vertical handover decisions with awareness of the related supporting networks and service characteristics.Since the decision process is executed with consideration of BRPM predictions,the SPVH algorithm can avoid congestion in HWN through a proactive method.The experiment results show that the proposed SPVH can solidly enhance the system performance in terms of service access ratio,average access delay,system throughput,usage ratio of spectrum resource,and eventually achieve higher network utility.

A Dependent-Chance Programming Model for Proactive Scheduling

Proactive scheduling based on expected value model is an effective method to develop robust schedules in consideration of minimizing project cost caused by deviations between realized and planed activity starting times.However,these schedules may be realized with low probabilities.In this paper,a novel model based on dependent-chance programming(DCP) is proposed,considering probability as well as solution robustness.A hybrid intelligent algorithm integrating stochastic simulation and genetic algorithm(GA)is designed to solve the proposed model.Moreover,a numerical example is conducted to reveal the effectiveness of the proposed model and the algorithm.