Adaptive Protocol Research Articles

SYNTHESIZING AI'S IMPACT ON CYBERSECURITY IN TELECOMMUNICATIONS: A CONCEPTUAL FRAMEWORK

As the telecommunications sector increasingly relies on interconnected digital infrastructure, the proliferation of cyber threats poses significant challenges to security and operational integrity. This review presents a conceptual framework for understanding and harnessing the potential of artificial intelligence (AI) in fortifying cybersecurity within the telecommunications industry. The framework integrates the transformative capabilities of AI with the unique demands of cybersecurity in telecommunications, aiming to enhance threat detection, mitigation, and response strategies. It encompasses a multidimensional approach that encompasses both technical and organizational facets, recognizing the interconnectedness of technology, human factors, and regulatory environments. Firstly, the framework delves into the application of AI in bolstering proactive threat intelligence gathering and analysis. Through advanced algorithms and machine learning techniques, AI empowers telecom operators to identify anomalous patterns, predict potential vulnerabilities, and pre-emptively adapt defensive measures. Secondly, it explores AI-driven solutions for dynamic risk assessment and adaptive cybersecurity protocols. By leveraging real-time data analytics and automated decision-making, telecom networks can swiftly adapt to evolving threats and ensure continuous protection against intrusions or breaches. Furthermore, the framework emphasizes the role of AI in augmenting human capabilities through intelligent automation and cognitive assistance. By offloading routine tasks and providing context-aware insights, AI enables cybersecurity professionals to focus on strategic initiatives and complex threat scenarios. Lastly, the framework addresses the imperative of ethical considerations, accountability, and transparency in deploying AI for cybersecurity in telecommunications. It advocates for responsible AI governance frameworks that prioritize privacy, fairness, and bias mitigation while fostering collaboration across industry stakeholders. In summary, this conceptual framework provides a roadmap for harnessing AI's transformative potential to fortify cybersecurity resilience in telecommunications, thereby safeguarding critical infrastructure and ensuring the integrity of global communication networks.
 Keywords: AI, Cybersecurity, Telecommunication, Framework, Conceptual, Impact, Review.

Research on adaptive practical prescribed-time consensus of multiple mechanical systems with full-state constraints

In this paper, an adaptive practical prescribed-time consensus (PPTC) for multiple mechanical systems with full-state constraints is discussed. We first propose a new nonlinear mapping (NM). By transforming the full state–constrained system with the NM, we can obtain an unconstrained system. Then combined with neural networks, graph theory, and practical prescribed-time control theory, a distributed adaptive PPTC protocol is proposed for the unconstrained system, which can ensure that position errors and speed errors reach a certain region within a prescribed-time and full-state constraints are satisfied. Finally, an example is given to demonstrate that this method can be implemented.

Attack reconstruction‐based resilient consensus tracking for multi‐agent systems with distributed adaptive control protocol

AbstractThis article considers the distributed secure consensus tracking control problem for multi‐agent systems (MASs) with relative output information. To tackle the potential false‐data‐injection (FDI) attacks on both the communication between physical components and the control center at the agent level, as well as the message transmission between connected agents, local sliding mode observers (SMO) and distributed observers are proposed for each agent. By introducing reconstructed signals for attacks and smooth terms to compensate the unknown input in the leader agent's dynamics, a distributed adaptive consensus protocol with relative output information is proposed. The closed‐loop stability is analyzed by introducing a novel Lyapunov function. It is shown that all closed‐loop signals are globally uniformly bounded and asymptotically consensus tracking can be achieved. Simulation results are provided to validate the theoretical findings.

Adaptive Data Transmission Protocols for Energy Harvesting WSNs Used in Agriculture

Energy consumption is a major concern in wireless sensor networks (WSNs) as it affects the lifespan of sensor nodes. Battery-based WSNs have a short operating period, which makes them impractical for real-time applications, for instance in agriculture. Energy harvesting and suitable medium access control (MAC) protocols have been used to extend the lifetime of nodes. Receiver-initiated protocols have been proved to be the best solution for energy harvesting WSNs. However, they suffer from a key disadvantage, i.e. an increase in collision rate. These collisions need to be reduced using a multi-layer protocol structure. In such a context, a new solar-based hybrid MAC (SHMAC) protocol relying on receiver-initiation and characterized by a multi-layer structure is proposed. It is an adaptive protocol capable of adapting to changing weather conditions. The nodes with a high energy harvesting rate have a higher level of residual energy and are active for longer time periods compared with those with low energy harvesting characteristics. The proposed work has shown improvements in two major MAC layer parameters, i.e. collision rate and energy neutrality operation ratio (ENO).

Challenges in the implementation of patient identification and the Gender Identity Law in healthcare institutions in Buenos Aires

Introduction: patient identification is a key component of Patient Safety goals. In the context of gender identity (GI) regulations, the adaptation of identification protocols is required for compliant implementation. Objective: to identify challenges and tensions in patient identification as a safety goal and its intersection with the current gender identity legislation in Argentina.Methods: a qualitative approach was used to collect data from seven healthcare institutions with patient admissions, selected based on their different profiles in terms of sector (public/private), patient safety accreditation process, and type of care (specialized/general). Grounded theory was employed to identify common institutional patterns.Results: three institutional situations were identified: 1. Contradiction: where compliance with GI regulations is perceived to undermine secure patient identification; 2. Potential convergence: although GI regulations are not fully implemented in patient identification, institutions deploy informal strategies to comply with them; 3. Convergence: institutions that have made changes to records and systems in line with GI. All institutions acknowledge the need for training in the care of transgender, transvestite, and non-binary patients.Conclusions: strengthening institutional policies based on safety goals and adherence to gender identity legislation is necessary. Organizational changes are essential, and training is needed to address the care of transgender, transvestite, and non-binary patients effectively

Effects of Early Weaning on Performance and Carcass Quality of Nellore Young Bulls.

This study compared early weaning (EW; 150 days) with conventional weaning (CW; 240 days) in Nellore young bulls, evaluating performance, carcass characteristics, and meat quality. A total of 74 non-castrated male calves were divided into two weaning strategies: EW (n = 37) and CW (n = 37). During the growth phase, which lasted 454 ± 14 d for EW calves and 359 ± 16 d for CW calves, animals received a protein-energy supplement at a ratio of 5 g per kg of body weight while grazing Brachiaria brizantha cv. Marandu. The animals were managed for an 87d finishing phase in three collective feedlot pens, with a 3-week adaptation protocol, starting with corn silage to a concentrate ratio of 55:45 and reaching a ratio of 30:70 in the final diet. Body weight, average daily gain (ADG), dry matter intake (DMI), feed efficiency (FE), carcass characteristics, and meat quality were evaluated. The EW group was approximately 44 kg lighter than the CW at the time of conventional weaning (p < 0.001). However, this weight difference did not influence ADG, DMI, and FE in the finishing phase. No significant differences were observed in carcass characteristics such as yield percentage, loin area, subcutaneous fat thickness, and meat quality, except for the weight of primal cuts, which was greater in the CW group (p < 0.001). Thus, although calves weaned early are lighter throughout subsequent production phases than those weaned conventionally, performance, efficiency, carcass yield, and meat quality are not affected.

Proportional integral observer‐based robust fault‐tolerant consensus for nonlinear two‐time‐scale‐agent systems with heterogeneous sensor faults

AbstractThis article studies the fault‐tolerant consensus issue of a class of nonlinear two‐time‐scale‐agent systems with heterogeneous sensor faults and external disturbances. First, the decentralized proportional integral (PI) observer for each agent is constructed to estimate the states and sensor faults simultaneously. Then, a distributed adaptive protocol based on the decentralized PI observer is designed to guarantee the consensus of the underlying systems. Some sufficient existence conditions are given in terms of linear matrix inequalities (LMIs) for the decentralized PI observer and the fault tolerant consensus protocol. Note that performance index is employed to attenuate the influence of sensor faults and disturbances on state estimation and the consensus of the underlying systems. Finally, the effectiveness and superiority of the proposed method are demonstrated by an application example and a numerical example.

Inequity in the face of success: understanding geographic and wealth-based equity in success of facility-based delivery for under-5 mortality reduction in six countries

BackgroundBetween 2000–2015, many low- and middle-income countries (LMICs) implemented evidence-based interventions (EBIs) known to reduce under-5 mortality (U5M). Even among LMICs successful in reducing U5M, this drop was unequal subnationally, with varying success in EBI implementation. Building on mixed methods multi-case studies of six LMICs (Bangladesh, Ethiopia, Nepal, Peru, Rwanda, and Senegal) leading in U5M reduction, we describe geographic and wealth-based equity in facility-based delivery (FBD), a critical EBI to reduce neonatal mortality which requires a trusted and functional health system, and compare the implementation strategies and contextual factors which influenced success or challenges within and across the countries.MethodsTo obtain equity gaps in FBD coverage and changes in absolute geographic and wealth-based equity between 2000–2015, we calculated the difference between the highest and lowest FBD coverage across subnational regions and in the FBD coverage between the richest and poorest wealth quintiles. We extracted and compared contextual factors and implementation strategies associated with reduced or remaining inequities from the country case studies.ResultsThe absolute geographic and wealth-based equity gaps decreased in three countries, with greatest drops in Rwanda – decreasing from 50 to 5% across subnational regions and from 43 to 13% across wealth quintiles. The largest increases were seen in Bangladesh – from 10 to 32% across geography – and in Ethiopia – from 22 to 58% across wealth quintiles. Facilitators to reducing equity gaps across the six countries included leadership commitment and culture of data use; in some countries, community or maternal and child health insurance was also an important factor (Rwanda and Peru). Barriers across all the countries included geography, while country-specific barriers included low female empowerment subnationally (Bangladesh) and cultural beliefs (Ethiopia). Successful strategies included building on community health worker (CHW) programs, with country-specific adaptation of pre-existing CHW programs (Rwanda, Ethiopia, and Senegal) and cultural adaptation of delivery protocols (Peru). Reducing delivery costs was successful in Senegal, and partially successful in Nepal and Ethiopia.ConclusionVariable success in reducing inequity in FBD coverage among countries successful in reducing U5M underscores the importance of measuring not just coverage but also equity. Learning from FBD interventions shows the need to prioritize equity in access and uptake of EBIs for the poor and in remote areas by adapting the strategies to local context.

Radiographers’ perspectives on interactional processes during older persons diagnostic medical imaging encounters: a qualitative study

BackgroundWithin a diagnostic medical imaging context, an interaction encompasses communication, physical contact and emotional support. These intricacies are an integral part in achieving a successful medical imaging outcome. An increasing ageing population presents unique challenges and leads to a higher demand for medical imaging services. There is a paucity of literature exploring the specialised knowledge and skills required by radiographers to service optimal person-centred care for elderly patients. The purpose of the study was to explore radiographers’ perspectives on interactional processes during older persons diagnostic medical imaging encounters.MethodsThe study used a qualitative exploratory research design with a descriptive approach to gain insights from 12 purposively sampled Australian radiographers, through open-ended interviews conducted online or by telephone. Verbatim transcripts were produced, and a thematic analysis employed until data saturation had been reached.ResultsThe three themes that emerged from the data analysis were: (1) optimising care and communication, (2) expectations and preconceptions and (3) physical and emotional comfort and safety. Generally, the approach to undertaking older persons examinations entailed more adaptive and flexible competencies and skills in comparison to the familiarised routine diagnostic medical imaging encounters with the younger cohort. Radiographers shared aspects on striking a balance between efficiency and proficiency with the elderly patient needs, preferences, values, safety and well-being considerations. This required swift, complex decision-making and judgement calls due to the unpredictable nature of the context in which the elderly person was situated. The result was the adaptation of examination protocols through equipment manipulation, with minimal disruptions to emotional and physical comfort, achieved through interventions and support strategies.ConclusionThe results highlight the many considerations for radiographers during a short clinical interaction. There is optimism in adding value to the elderly persons experience through a complex interactional process. It is anticipated that the identified skills will inform on best practice principles to achieve an elderly person-centred care medical imaging outcome.

Effectiveness of Counseling on Long-Term Contraceptive Methods through Leaflets during the Covid-19 Pandemic

The Covid-19 pandemic in Indonesia is currently entering a new normal period or the implementation of the New Habit Adaptation protocol. This condition has reduced the number of family planning participation so that it is feared that it could cause a baby boom or an increase in the number of pregnancies and births. For this reason, serious efforts need to be made in order to increase the number of family planning participation again. During this Covid-19 pandemic, as much as possible should avoid crowds so that cases of Covid-19 transmission do not occur. One of the efforts that can be done is through counseling with leaflet media. This study aims to determine the effectiveness of health education using media leaflets about long-term contraceptive methods during the new normal for women of childbearing age. The study was conducted in Leran Village with a total population of 1, 506 then obtained the number of samples as many as 316 respondents. Sampling technique using probability sampling with proportional random sampling technique. This type of research is a quasi-experimental with pretest-posttest one group design. Data analysisused the Wilcoxon test to see the effectiveness anddetermine the difference before and after giving counseling.The result of this research is that there is an effect after it is donecounseling with leaflet media on women of childbearing age knowledge in Leran Village. It is hoped that the role of health workers and health cadres will always carry out promotions and education about the benefits of family planning, especially during the Covid-19 pandemic.

Advancing Wireless Sensor Networks through Performance Evaluation of M-PDCH Routing Protocol for Enhanced Quality of Service

Objective: The decisive aim of this investigation is to improve the capabilities and limitations of PEGASIS with Double Cluster Head (PDCH), for enhancing the overall Quality of Service (QoS) in Wireless Sensor Networks (WSNs). Methods: This research is intended at the application of efficient routing protocol for wireless sensor networks. It works on the principle of the formation of cluster head and clustering. This is accomplished to achieve high QoS for WSN. Improving the efficacy of a WSN protocol is decisive for optimizing communication, resource utilization, and overall effectiveness. An innovative and novel protocol named Mobile-PDCH (M-PDCH) has been devised, developed, and tested. Here several parameters have been carefully investigated for enhancing the performance of a WSN protocol such as energy consumption, delay, and packet loss. A simulation environment has been created to evaluate, compare, and validate the performance and to suggest the desired applications of the proposed protocol. Findings: In the hierarchical category, PDCH performs better compared to all the other protocols. But it suffers from high packet drop, which decrease the performance of the protocol. To improve the performance of sensor networks, there is a need for adaptive routing protocol. The examination of simulation outcomes for the recommended protocol, M-PDCH, has been conducted in comparison with PDCH. The findings indicate that the protocol exhibits superior performance. The proposed algorithm improves the packet drop by 29.75%, reduces delay by 23.28%, and lowers energy consumption by 19.18% when compared to PDCH. Novelty: A novel adaptive routing protocol termed M-PDCH has been proposed for the enhancement of the WSN life span and durability of the sensor nodes. The simulation results show that the proposed algorithm produces better results compared to PDCH protocol. The various QoS parameter results are compared, verified, and validated with existing protocol PDCH. Keywords: WSN, PDCH, Design issues, Metrics, QoS, HRP

Development of a reverse transcriptase digital droplet polymerase chain reaction-based approach for SARS-CoV-2 variant surveillance in wastewater.

An urgent need for effective surveillance strategies arose due to the global emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although vaccines and antivirals are available, concerns persist about the evolution of new variants with potentially increased infectivity, transmissibility, and immune evasion. Therefore, variant monitoring is crucial for public health decision-making. Wastewater-based surveillance has proven to be an effective tool to monitor SARS-CoV-2 variants within populations. Specific SARS-CoV-2 variants are detected and quantified in wastewater in this study using a reverse transcriptase digital droplet polymerase chain reaction (RT-ddPCR) approach. The 11 designed assays were first validated in silico using a substantial dataset of high-quality SARS-CoV-2 genomes to ensure comprehensive variant coverage. The assessment of the sensitivity and specificity with reference material showed the capability of the developed assays to reliably identify target mutations while minimizing false positives and false negatives. The applicability of the assays was evaluated using wastewater samples from a wastewater treatment plant in Ghent, Belgium. The quantification of the specific mutations linked to the variants of concern present in these samples was calculated using these assays based on the detection of single mutations, which confirms their use for real-world variant surveillance. In conclusion, this study provides an adaptable protocol to monitor SARS-CoV-2 variants in wastewater with high sensitivity and specificity. Its potential for broader application in other viral surveillance contexts highlights its added value for rapid response to emerging infectious diseases. PRACTITIONER POINTS: Robust RT-ddPCR methodology for specific SARS-CoV-2 variants of concern detection in wastewater. Rigorous validation that demonstrates high sensitivity and specificity. Demonstration of real-world applicability using wastewater samples. Valuable tool for rapid response to emerging infectious diseases.

Strategy for Biobanking of Ovarian Cancer Organoids: Addressing the Interpatient Heterogeneity across Histological Subtypes and Disease Stages

While the establishment of an ovarian cancer biobank from patient-derived organoids along with their clinical background information promises advances in research and patient care, standardization remains a challenge due to the heterogeneity of this lethal malignancy, combined with the inherent complexity of organoid technology. This adaptable protocol provides a systematic framework to realize the full potential of ovarian cancer organoids considering a patient-specific variability of progenitors. By implementing a structured experimental workflow to select optimal culture conditions and seeding methods, with parallel testing of direct 3D seeding versus a 2D/3D route, we obtain, in most cases, robust long-term expanding lines suitable for a broad range of downstream applications. Notably, the protocol has been tested and proven efficient in a great number of cases (N = 120) of highly heterogeneous starting material, including high-grade and low-grade ovarian cancer and stages of the disease with primary debulking, recurrent disease, and post-neoadjuvant surgical specimens. Within a low Wnt, high BMP exogenous signaling environment, we observed progenitors being differently susceptible to the activation of the Heregulin 1 ß (HERß-1)-pathway, with HERß-1 promoting organoid formation in some while inhibiting it in others. For a subset of the patient's samples, optimal organoid formation and long-term growth necessitate the addition of fibroblast growth factor 10 and R-Spondin 1 to the medium. Further, we highlight the critical steps of tissue digestion and progenitor isolation and point to examples where brief cultivation in 2D on plastic is beneficial for subsequent organoid formation in the Basement Membrane Extract type 2 matrix. Overall, optimal biobanking requires systematic testing of all main conditions in parallel to identify an adequate growth environment for individual lines. The protocol also describes the handling procedure for efficient embedding, sectioning, and staining to obtain high-resolution images of organoids, which is required for comprehensive phenotyping.

Unprecedented Rise of Mucormycosis in COVID-19 Patients: Urgent Need for Protocol Adaptation and Awareness in India – A Review

Mucormycosis, a rare fungal infection, has seen a concerning surge in incidence among COVID-19 patients in India. Unlike infectious diseases, Mucormycosis spreads through fungal spores ubiquitous in the environment. COVID-19 patients with diabetes are particularly susceptible, presenting symptoms such as headache, fever, eye pain, nasal congestion, and vision loss. Early diagnosis is crucial for successful treatment. Management involves a multidisciplinary approach, including antifungal medications like liposomal amphotericin-B and posaconazole. However, treatment challenges arise due to limited availability, high cost, and prolonged administration of these drugs. Monitoring blood glucose levels during steroid therapy and raising awareness among healthcare workers and patients are essential preventive measures. Improved ventilation and hygiene practices in hospitals can reduce the risk of exposure to fungal spores. Early detection and prompt treatment are vital in preventing severe outcomes of Mucormycosis. Public education and environmental control measures are essential to mitigate the increasing incidence of this life-threatening fungal infection.

Adaptation-induced sharpening of orientation tuning curves in the mouse visual cortex.

Orientation selectivity is an emergent property of visual neurons across species with columnar and noncolumnar organization of the visual cortex. The emergence of orientation selectivity is more established in columnar cortical areas than in noncolumnar ones. Thus, how does orientation selectivity emerge in noncolumnar cortical areas after an adaptation protocol? Adaptation refers to the constant presentation of a nonoptimal stimulus (adapter) to a neuron under observation for a specific time. Previously, it had been shown that adaptation has varying effects on the tuning properties of neurons, such as orientation, spatial frequency, motion and so on. We recorded the mouse primary visual neurons (V1) at different orientations in the control (preadaptation) condition. This was followed by adapting neurons uninterruptedly for 12 min and then recording the same neurons postadaptation. An orientation selectivity index (OSI) for neurons was computed to compare them pre- and post-adaptation. We show that 12-min adaptation increases the OSI of visual neurons ( n = 113), that is, sharpens their tuning. Moreover, the OSI postadaptation increases linearly as a function of the OSI preadaptation. The increased OSI postadaptation may result from a specific dendritic neural mechanism, potentially facilitating the rapid learning of novel features.

Pulse Electrolysis Turns on CO2 Methanation through N‐Confused Cupric Porphyrin

AbstractBreaking the D4h symmetry in the square‐planar M−N4 configuration of macrocycle molecular catalysts has witnessed enhanced electrocatalytic activity, but at the expense of electrochemical stability. Herein, we hypothesize that the lability of the active Cu−N3 motifs in the N‐confused copper (II) tetraphenylporphyrin (CuNCP) could be overcome by applying pulsed potential electrolysis (PPE) during electrocatalytic carbon dioxide reduction. We find that applying PPE can indeed enhance the CH4 selectivity on CuNCP by 3 folds to reach the partial current density of 170 mA cm−2 at &gt;60 % Faradaic efficiency (FE) in flow cell. However, combined ex situ X‐ray diffraction (XRD), transmission electron microscope (TEM), and in situ X‐ray absorption spectroscopy (XAS), infrared (IR), Raman, scanning electrochemical microscopy (SECM) characterizations reveal that, in a prolonged time scale, the decomplexation of CuNCP is unavoidable, and the promoted water dissociation under high anodic bias with lowered pH and enriched protons facilitates successive hydrogenation of *CO on the irreversibly reduced Cu nanoparticles, leading to the improved CH4 selectivity. As a key note, this study signifies the adaption of electrolytic protocol to the catalyst structure for tailoring local chemical environment towards efficient CO2 reduction.

Pulse Electrolysis Turns on CO2 Methanation through N-Confused Cupric Porphyrin.

Breaking the D4h symmetry in the square-planar M-N4 configuration of macrocycle molecular catalysts has witnessed enhanced electrocatalytic activity, but at the expense of electrochemical stability. Herein, we hypothesize that the lability of the active Cu-N3 motifs in the N-confused copper (II) tetraphenylporphyrin (CuNCP) could be overcome by applying pulsed potential electrolysis (PPE) during electrocatalytic carbon dioxide reduction. We find that applying PPE can indeed enhance the CH4 selectivity on CuNCP by 3 folds to reach the partial current density of 170 mA cm-2 at >60 % Faradaic efficiency (FE) in flow cell. However, combined ex situ X-ray diffraction (XRD), transmission electron microscope (TEM), and in situ X-ray absorption spectroscopy (XAS), infrared (IR), Raman, scanning electrochemical microscopy (SECM) characterizations reveal that, in a prolonged time scale, the decomplexation of CuNCP is unavoidable, and the promoted water dissociation under high anodic bias with lowered pH and enriched protons facilitates successive hydrogenation of *CO on the irreversibly reduced Cu nanoparticles, leading to the improved CH4 selectivity. As a key note, this study signifies the adaption of electrolytic protocol to the catalyst structure for tailoring local chemical environment towards efficient CO2 reduction.

Subthalamic nucleus dynamics track microlesion effect in Parkinson's disease.

Parkinson's Disease (PD) is characterized by the temporary alleviation of motor symptoms following electrode implantation (or nucleus destruction), known as the microlesion effect (MLE). Electrophysiological studies have explored different PD stages, but understanding electrophysiological characteristics during the MLE period remains unclear. The objective was to examine the characteristics of local field potential (LFP) signals in the subthalamic nucleus (STN) during the hyperacute period following implantation (within 2days) and 1month post-implantation. 15 patients diagnosed with PD were enrolled in this observational study, with seven simultaneous recordings of bilateral STN-LFP signals using wireless sensing technology from an implantable pulse generator. Recordings were made in both on and off medication states over 1month after implantation. We used a method to parameterize the neuronal power spectrum to separate periodic oscillatory and aperiodic components effectively. Our results showed that beta power exhibited a significant increase in the off medication state 1month after implantation, compared to the postoperative hyperacute period. Notably, this elevation was effectively attenuated by levodopa administration. Furthermore, both the exponents and offsets displayed a decrease at 1month postoperatively when compared to the hyperacute postoperative period. Remarkably, levodopa medication exerted a modulatory effect on these aperiodic parameters, restoring them back to levels observed during the hyperacute period. Our findings suggest that both periodic and aperiodic components partially capture distinct electrophysiological characteristics during the MLE. It is crucial to adequately evaluate such discrepancies when exploring the mechanisms of MLE and optimizing adaptive stimulus protocols.

Reinforcement Learning and PK-PD Models Integration to Personalize the Adaptive Dosing Protocol of Erdafitinib in Patients with Metastatic Urothelial Carcinoma.

The integration of pharmacokinetic-pharmacodynamic (PK-PD) modeling and simulations with artificial intelligence/machine learning algorithms is one of the most attractive areas of the pharmacometric research. These hybrid techniques are currently under investigation to perform several tasks, among which precision dosing. In this scenario, this paper presents and evaluates a new framework embedding PK-PD models into a reinforcement learning (RL) algorithm, Q-learning (QL), to personalize pharmacological treatment. Each patient is represented with a set of PK-PD parameters and has a personal QL agent which optimizes the individual treatment. In the training phase, leveraging PK-PD simulations, the QL agent assesses different actions, defined consistently with the clinical knowledge to consider only plausible dose-adjustments, in order to find the optimal rules. The proposed framework was evaluated to optimize the erdafitinib treatment in patients with metastatic urothelial carcinoma. This drug was approved by the US Food and Drug Administration (FDA) with a dose-adaptive protocol based on monitoring the levels of serum phosphate, which represent a biomarker of both treatment efficacy and toxicity. To evaluate the flexibility of the methodology, a heterogeneous virtual population of 141 patients was generated using an erdafitinib population PK (PopPK)-PD literature model. For each patient, treatment response was simulated by using both QL-optimized protocol and the clinical one. QL agents outperform the approved dose-adaptive rules, increasing more than 10% the efficacy and the safety of treatment at each end point. Results confirm the great potentialities of the integration of PopPK-PD models and RL algorithms to optimize precision dosing tasks.

Low-complexity adaptive reconciliation protocol for continuous-variable quantum key distribution

In continuous-variable quantum key distribution systems, reconciliation is a crucial step that significantly affects the secret key rate (SKR). The rateless protocol based on Raptor codes can achieve high reconciliation efficiency at low signal-to-noise ratios (SNRs). However, the high complexity of low-density parity-check (LDPC) codes used for the precoding in Raptor codes limits the speed of reconciliation. In this paper, we propose an adaptive reconciliation protocol by modifying Raptor codes. The length of random binary sequences is increased because we remove the LDPC precoding that adds redundancy. The modified Raptor codes reduce the complexity of encoding with better performance. The proposed protocol gives a reconciliation efficiency higher than 98.1% in the SNR below −20 dB and maintains a certain SKR in long-distance transmission.