bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dual‐Stimuli‐Activatable Hybrid Prodrug for the Self‐Immolative Delivery of an Anticancer Agent and Hydrogen Sulfide with Turn‐On Fluorescence
Authors: Sufian Abu , Badirujjaman Md. , Barman Pallavi , Bhabak Krishna P. 
Published: September 2023

AbstractStimuli‐responsive fluorogenic prodrugs are advantageous for the targeted drug delivery enabling real‐time non‐invasive monitoring with turn‐on fluorescence. We report herein the dual‐stimuli (ROS and CA)‐responsive thiocarbamate‐based prodrug (AM‐TCB) for the turn‐on fluorogenic delivery of the naphthalimide‐based anticancer agent amonafide along with the gasotransmitter hydrogen sulfide (H2S). A carbamate‐based prodrug AM‐CB was also designed, capable of releasing the anticancer agent amonafide without any H2S. The prodrugs were synthesized using multi‐step organic synthesis. UV‐Vis and fluorescence spectroscopic studies revealed selective reactivity of the boronate ester group of prodrugs towards ROS (primarily H2O2) with the release of amonafide and COS/CO2 via self‐immolative processes. Hydrolysis of the generated COS by carbonic anhydrase (CA) produces H2S. While the prodrug AM‐TCB retained the anticancer activity of free amonafide in cancer cells (MDA‐MB‐231 and HeLa), unlike amonafide, it enhanced the cellular viability of the non‐malignant cells (HEK‐293). Fluorescence imaging in HeLa cells revealed the simultaneous delivery of the anticancer agent and H2S from AM‐TCB with turn‐on fluorescence. Western blot studies further revealed the cytoprotective effects of the released H2S from AM‐TCB. The present adjuvant strategy therefore would be helpful in future for ameliorating the anticancer drug‐induced side‐effects.
Transition‐Metal‐Catalyzed Addition of Organosulfur Compounds to Alkynes and Alkenes: Catalysis and Catalyst Poisons
Authors: Yamamoto Yuki , Ogawa Akiya 
Published: September 2023

AbstractThe addition of heteroatom compounds to alkynes and alkenes is an atom‐efficient method of carbon‐heteroatom bond formation and is widely used as a fundamental synthetic method for the construction of functional molecules. Nevertheless, examples of transition‐metal‐catalyzed addition reactions of group 16 heteroatom compounds to carbon‐carbon unsaturated bonds have been limited due to the widespread belief that organic sulfur and selenium compounds are representative catalyst poisons. In recent decades, however, several seminal catalytic reactions of sulfur compounds have been developed, providing important insights into catalysis and poisons. Therefore, this paper focuses on the transition‐metal‐catalyzed addition of organosulfur compounds to alkynes and alkenes, gains comprehensive insights into the catalysis and catalyst poisons, and proposes concepts for the development of transition‐metal‐catalyzed reactions of group 16 heteroatom compounds.
Evaluation of patient‐reported outcome measures for on‐demand treatment of hereditary angioedema attacks and design of KONFIDENT, a phase 3 trial of sebetralstat
Authors: Cohn Danny M. , Aygören‐Pürsün Emel , Bernstein Jonathan A. , Farkas Henriette , Lumry William R. , Maurer Marcus , Zanichelli Andrea , Iverson Matthew , Hao James , Smith Michael D. , Yea Christopher M. , Audhya Paul K. , Riedl Marc A. 
Published: September 2023

AbstractBackgroundHereditary angioedema (HAE) with C1‐inhibitor deficiency (HAE‐C1‐INH) is characterized by recurrent, debilitating episodes of swelling. Sebetralstat, an investigational oral plasma kallikrein inhibitor, demonstrated promising efficacy for on‐demand treatment of HAE‐C1‐INH in a phase 2 trial. We describe the multipronged approach informing the design of KONFIDENT, a phase 3 randomized, placebo‐controlled, three‐way crossover trial evaluating the efficacy and safety of sebetralstat in patients aged ≥12 years with HAE‐C1‐INH.MethodsTo determine an optimal endpoint to measure the beginning of symptom relief in KONFIDENT, we engaged patients with HAE on clinical outcome measures and subsequently conducted analyses of phase 2 outcomes. Sample size was determined via a simulation‐based approach using phase 2 data.ResultsPatient interviews revealed a strong preference (71%) for the Patient Global Impression of Change (PGI‐C) over other measures and indicated a rating of “A Little Better” as a clinically meaningful milestone. In phase 2, a rating of “A Little Better” demonstrated agreement with attack severity improvement and resolution on the Patient Global Impression of Severity and had better sensitivity than “Better.” Simulations indicated that 84 patients completing treatment would ensure at least 90% power for assessing the primary endpoint of time to beginning of symptom relief defined as a PGI‐C rating of at least “A Little Better” for two time points in a row.ConclusionsPatient feedback and phase 2 data support PGI‐C as the primary outcome measure in the phase 3 KONFIDENT trial evaluating sebetralstat, which has the potential to be the first oral on‐demand treatment for HAE‐C1‐INH attacks.
CuO/Cu2O‐Coated Cu2S Nanowire Arrays: Effects of Thermal Annealing on Thermal Stability and Optical Properties
Authors: Li Liqiang , Zhang Wenxing , Li Peng 
Published: September 2023

AbstractCuO/Cu2O‐coated Cu2S nanowire arrays with an average diameter of 180 and 280 nm are prepared by the solid–gas reaction. The crystallinity of the oxide improves with increasing annealing temperature from 100 to 500 °C, whereas the melting point of the Cu2S nanowire arrays decreases with decreasing nanowire diameter (always less than that of bulk Cu2S, 1100 °C). The annealing temperature should be less than 500 °C for oxide‐coated Cu2S nanowire arrays that have an average diameter less than 180 nm, but can reach 500 °C for nanowire arrays that have an average diameter greater than 280 nm. Thermal annealing can improve the crystallinity of the oxide and optimize the optical properties of oxide‐coated Cu2S nanowire arrays. This research lays a foundation for direct application of CuO/Cu2O‐coated Cu2S nanowire arrays in photovoltaic and lithium‐ion batteries.
MirroredK‐AryN‐Tree and its efficiency of fault tolerance
Authors: Li Yamin , Chu Wanming 
Published: September 2023

SummaryFat‐tree is one of the most commonly used topologies in the interconnection networks of modern supercomputers and datacenters. In a traditional fat‐tree,k‐aryn‐tree for instance, the degree of root switches is less than that of other switches. Fat‐tree is a folded version of a Clos network. A Clos network uses the same degree switches in all stages. However, fat‐tree or Clos network has a high switch cost and great packet latency. This paper introduces a MirroredK‐AryN‐Tree (MiKANT) network and presents switch fault‐tolerant routing algorithms for it. Compared withk‐aryn‐trees and Clos networks, MiKANT connects more compute nodes with fewer switches and links so that it can be implemented at a lower hardware cost, it uses switches that have the same number of ports to keep the regularity, and it shortens the average distance to reduce the packet latency for achieving higher communication performance. We give three simple deadlock‐free switch fault‐tolerant routing algorithms for MiKANT and evaluate their performance. The simulation results show that the proposed algorithms achieve much higher performance than the shortest path routing algorithm. Although MiKANT uses fewer switches and links than fat‐tree, the simulation result shows that it has an almost the same successful routing ratio as the fat‐tree for the switch fault tolerance.
Mitigating cyclostationary noise using multi‐fold turbo codes on a two‐user narrowband power‐line binary adder channel
Authors: Khalid Abbas , Adebisi Bamidele , Shan Rafi Us , Honary Bahram 
Published: September 2023

SummaryPower lines present a more challenging communication environment compared to other media. Impedance mismatches and network branches render the channel frequency‐selective, leading to strong inter‐symbol interference (ISI). Moreover, devices connected to the power grid introduce impulsive noise on the network. Such factors may degrade the system performance drastically. Therefore, robust coding and modulation schemes are required to increase the communication reliability. Furthermore, multiple access communication allows many users to share a common medium to enhance the systems' throughput. This paper examines the behaviour of two schemes, turbo codes and multi‐fold turbo codes, against a two‐user adder channel under power‐line conditions operating below 500 kHz. Both schemes employ distinct codes for each user and make use of orthogonal frequency‐division multiplexing (OFDM) to cope with the ISI. Three configurations of a low‐voltage (LV) power‐line outdoor network are considered. Results obtained through simulations show that a gain, up to 3 dB, can be obtained for both users using the multi‐fold turbo coding over the conventional turbo coding. The effect of iterative decoding on the performance of both schemes is also reported.
Green fault detection scheme for IoT‐enabled wireless sensor networks
Authors: Chanak Prasenjit , Banerjee Indrajit , Bose Sagar 
Published: September 2023

SummaryWireless sensor network (WSN) is one of the major components for the Internet of Things (IoT)‐based smart systems that accumulate meaningful information and send them to the end‐user. In IoT‐enabled WSNs, large numbers of sensor nodes are deployed in an on‐site environment to collect and transmit different physical parameters from the monitoring environments to a central repository. However, low‐cost sensing devices in IoT‐enabled WSNs are prone to fail due to energy depletion, software failures, and hardware failures. The existing fault detection approaches consume notable additional energy to detect and overcome the failures. As a result, the whole network is subject to premature death. This article proposes a green fault detection scheme for IoT‐enabled WSNs to detect faulty nodes and solve the premature death problem of the network. Furthermore, a faulty node reuse mechanism is proposed that significantly prolongs the network lifetime. We analyze the properties of the proposed algorithm mathematically and validate its performance through extensive simulation and real‐life experiments. The simulation and experimental results show improved performance of the proposed scheme in terms of fault detection accuracy, false alarm rate, and network lifetime.
A novel multiple access diamond channel model
Authors: Al‐qudah Zouhair , Al Bataineh Mohammad , Musa Ahmed 
Published: September 2023

SummaryThis paper introduces a new multiuser communication model, which we call multiple access diamond channel. In this channel model, many sources transmit their signals to a destination in the case of no direct links between the end terminals. Therefore, we employ two parallel relays to extend transmission to the destination. Further, we specifically characterize two different transmission schemes along with their respective achievable rate regions. Then, we develop an outer bound to the transmission in each scheme. Moreover, we present many numerical examples to mainly compare between the two different transmission schemes and to distinguish the case for which we attain the capacity region.
An optimized clustering using hybrid meta‐heuristic approach for wireless sensor networks
Authors: V Rajaram , N Kumaratharan 
Published: September 2023

SummaryPower efficiency is one of the major attributes that has to be concentrated in wireless sensor network (WSN). Efficiency in the consumption of power is achieved by clustering, routing, and balancing the load in the network. The proposed work focuses on clustering to balance the load in the network, which in turn improves the power consumption by the sensor nodes. Clustering is one of the prominent techniques in WSN where research is still going on to improve efficiency. In the proposed work, the sensor nodes are collected together for the formation of multiple groups called as clusters. Cluster heads are selected using efficient satin bower bird optimization algorithm where the weight of the node is taken as a parameter. Among all these multiple cluster heads, the highly powered cluster heads are named as chief cluster head utilizing crow search optimization. In a multihop manner, the sensor nodes sense the collected data to the cluster heads, which in turn send the aggregated data to the chief cluster heads. All the selected chief cluster heads send the collected data to the central server node. Simulation is carried out in MATLAB R2020a and the performance of the proposed heuristic‐based clustering is compared with other clustering protocols in terms of energy efficiency, throughput, and delivery ratio, and it is verified that the proposed protocol gives better results.
A novel discrete cuckoo search algorithm‐based selective mapping technique to minimize the peak‐to‐average power ratio of universal filtered multicarrier signal
Authors: Şimşir Şakir , Taşpınar Necmi 
Published: September 2023

SummaryThe universal filtered multicarrier (UFMC), which has emerged as a product of the intensive studies carried out for developing alternative waveforms compatible with the oncoming fifth generation (5G) technology, has rapidly become one of the few waveforms considered seriously to be utilized in the next generation telecommunication systems due to its exclusive features. However, high peak‐to‐average power ratio (PAPR) problem specific to the multicarrier waveforms is waiting for researchers as the primary issue to be tackled in the UFMC waveform. To address this issue, an efficient PAPR reduction scheme called discrete cuckoo search algorithm‐based selective mapping (DCS‐SLM) is suggested in this paper. While creating the proposed DCS‐SLM scheme, in order to make the original CS algorithm suitable to be integrated into the conventional SLM method, a novel DCS algorithm was developed. Thanks to the related DCS algorithm, it becomes possible in the SLM technique to perform phase sequence optimization, which is a combinatorial optimization process that can be carried out in discrete space. It is clearly observed from the simulation results that the integration of our novel DCS algorithm to create a new PAPR reduction technique called DCS‐SLM leads to a remarkable performance improvement in the conventional SLM method due to the DCS‐based phase optimization through which the PAPR of UFMC signals are reduced to minimum levels.
Localizing non‐line‐of‐sight nodes in Vehicluar Adhoc Networks using gray wolf methodology
Authors: Kaviarasan Ramu , Harikrishna Pillutla 
Published: September 2023

SummaryVehicular ad hoc networks (VANETs) evolved by adopting the principles of mobile ad hoc networks. This network has been designed to deploy safety related application in vehicular node in the less chaotic environment in road scenarios. Vehicles exchange emergency messages through direct communication. In a practical situation, a direct communication between the vehicles is not possible, and it is prohibited by either static or dynamic obstacles. These obstacles prevent the direct communication between the vehicles and can craft a situation like non‐line of sight (NLOS). This NLOS becomes a perennial problem to the researchers as it creates localization and integrity issues which are considered to be important for road safety applications. Handling the moving obstacles is found to be a challenging one in the VANET environment as obstacles like truck are found to have similar characteristics of the vehicular nodes. This paper utilizes the merits of the meta‐heuristic approach and makes use of the improved gray wolf optimization algorithm for improving the localization and integrity services of the VANET by overcoming the NLOS conditions. The proposed methodology is found to have improved neighborhood awareness, reduced latency, improved emergency message delivery rate, and reduced mean square error rate.
Random forest classifier‐based safe and reliable routing for opportunistic IoT networks
Authors: Kandhoul Nisha , Dhurandher Sanjay K. , Woungang Isaac 
Published: September 2023

SummaryDesigning a safe and reliable way for communicating the messages among the devices and humans forming the Opportunistic Internet of Things network (OppIoT) has been a challenge since the broadcast mode of message sharing is used. To contribute toward addressing such challenge, this paper proposes a Random Forest Classifier (RFC)‐based safe and reliable routing protocol for OppIoT (called RFCSec) which ensures space efficiency, hash‐based message integrity, and high packet delivery, simultaneously protecting the network against safety threats viz. packet collusion, hypernova, supernova, and wormhole attacks. The proposed RFCSec scheme is composed of two phases. In the first one, the RFC is trained on real data trace, and based on the output of this training, the second phase consists in classifying the encountered nodes of a given node as belonging to one of the output classes of nodes based on their past behavior in the network. This helps in proactively isolating the malicious nodes from participating in the routing process and encourages the participation of the ones with good message forwarding behavior, low packet dropping rate, high buffer availability, and a higher probability of delivering the messages in the past. Simulation results using the ONE simulator show that the proposed RFCSec secure routing scheme is superior to the MLProph, RLProph, and CAML routing protocols, chosen as benchmarks, in terms of legitimate packet delivery, probability of message delivery, count of dropped messages, and latency in packet delivery. The out‐of‐bag error obtained is also minimal
New method of traffic flow forecasting based on quantum particle swarm optimization strategy for intelligent transportation system
Authors: Zhang Degan , Wang Jiaxu , Fan Hongrui , Zhang Ting , Gao Jinxin , Yang Peng 
Published: September 2023

SummaryTraffic flow forecasting is one of the essential means to realize smart cities and smart transportation. The accurate and effective prediction will provide an important basis for decision‐making in smart transportation systems. This paper proposes a new method of traffic flow forecasting based on quantum particle swarm optimization (QPSO) strategy for intelligent transportation system (ITS). We establish a corresponding model based on the characteristics of the traffic flow data. The genetic simulated annealing algorithm is applied to the quantum particle swarm algorithm to obtain the optimized initial cluster center, and is applied to the parameter optimization of the radial basis neural network prediction model. The function approximation of radial basis neural network is used to obtain the required data. In addition, in order to compare the performance of the algorithms, a comparison study with other related algorithms such as QPSO radial basis function (QPSO‐RBF) is also performed. Simulation results show that compared with other algorithms, the proposed algorithm can reduce prediction errors and get better and more stable prediction results.
A fault‐tolerant workflow management system with Quality‐of‐Service‐aware scheduling for scientific workflows in cloud computing
Authors: Ahmad Zulfiqar , Nazir Babar , Umer Asif 
Published: September 2023

SummaryCloud computing provides solutions to many scientific and business applications. Large‐scale scientific applications, which are structured as scientific workflows, are evaluated through cloud computing. In this paper, we proposed a Quality‐of‐Service‐aware fault‐tolerant workflow management system (QFWMS) for scientific workflows in cloud computing. We have considered two real‐time scientific workflows, i.e., Montage and CyberShake, for an evaluation of the proposed QFWMS. The results of the proposed QFWMS scheduling were evaluated through simulation environment WorkflowSim and compared with three well‐known heuristic scheduling policies: (a) minimum completion time (MCT), (b) Maximum‐minimum (Max‐min), and (c) Minimum‐minimum (Min‐min). By considering Montage scientific workflow, the proposed QFWMS reduces the make‐span 8.86%, 8.94%, and 5.53% compared with existing three heuristic policies. Similarly, the proposed QFWMS reduces the cost 6.19%, 3.52%, and 3.60% compared with existing three heuristic policies. Likewise, by considering CyberShake scientific workflow, the proposed QFWMS reduces the make‐span 19.54%, 21.41%, and 25.71% compared with existing three heuristic policies. Similarly, the proposed QFWMS reduces the cost 8.78%, 8.40%, and 8.61% compared with existing three heuristic policies. More so, for QFWMS, SLA is neither violated for time constraints nor for cost constraints. While for MCT, Max‐min and Min‐min scheduling policies, SLA is violated 32, 37, and 23 times, respectively. Conclusively, the proposed QFWMS scheduling and management system is one of the significant workflow management systems for execution and management of scientific workflows in cloud computing.
A self‐adaptive algorithm for super‐peer selection considering the mobility of peers in cognitive mobile peer‐to‐peer networks
Authors: Amirazodi Nahid , Saghiri Ali Mohammad , Meybodi Mohammad Reza 
Published: September 2023

SummaryCognitive peer‐to‐peer networks are obtained from a combination of cognitive networking concepts and peer‐to‐peer networks. These networks are able to improve their performance while operating under dynamic and unknown environments. A cognitive peer‐to‐peer network tries to learn an appropriate configuration for itself considering the unknown physical properties of peers. Cognitive mobile peer‐to‐peer networks refer to cognitive peer‐to‐peer networks which are built over mobile ad hoc networks. In these networks, heterogeneity of the mobility of peers and resource limitation in wireless networks create challenges for network management algorithms. Because of the dynamicity of these networks, the management algorithms should be designated in self‐adaptive manner. In one type of these networks, some peers, called super‐peers, undertake to perform network managerial tasks. The mobility of peers leads to connection failure among peers and reselection of new super‐peers. Therefore, the selection of super‐peers, due to their influential role, requires an algorithm that considers the peers' mobility. Up to now, no self‐adaptive algorithm has been designated for super‐peer selection considering the mobility of peers in a self‐adaptive manner. This paper proposes M‐SSBLA, a self‐adaptive algorithm for super‐peer selection considering the mobility of peers based on learning automata. The proposed algorithm is obtained from cooperation between a learning automata‐based cognitive engine and MIS. MIS is a well‐known super‐peer selection algorithm in mobile peer‐to‐peer networks. We compared the proposed algorithm with recently reported algorithms, especially for a network with high mobility. Simulation results show that the proposed algorithm can cover maximum ordinary‐peer with a few super‐peer and improve robustness against super‐peer failures while decreasing maintenance overhead.