bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigations on Iot Based Wsn With Swipt-noma Combination
Authors: Sixtus Reginald Jude , Muthu Tamilarasi
Published: July 2023

Wireless Communication provides the interconnection of different devices for the ubiquitous accessibility of intelligent capacity. Wireless Communication incorporates device interaction for the provision of sufficient capability in networking between intermediate devices. Conventionally, the Internet of Things (IoT) and Wireless Sensor Networks (WSN) offer sufficient information between intermediate devices. IoT-WSN devices are resource constraints (RC), compact devices, and limited resources of battery. The increase in the number of users leads to challenges with security in the IoT-WSN. The data transmission between the wireless communications uses the 5G communication-based NOMA communication. Due to limited RC features the computational complexity is higher with minimal consumption of space those are evaluated with embedded hardware features within the IoT – WSN. This paper aimed to develop an appropriate optimal routing simultaneous wireless information and power transfer based Long Short-Term Memory (ORSS). The proposed ORSS model uses the covariance matrix-based routing and security model. The performance of the proposed ORSS is evaluated for security analysis based on consideration of different attacks. With the ORSS model, the position of nodes is computed with the covariance matrix estimation. To identify the optimal route’s Particle Swarm Optimization (PSO) algorithm is implemented for the route scheduling for the data transmission. To minimize the energy consumption within the network SWIPT is implemented for effective energy harvesting. Based on the covariance estimation optimal routes in the network are computed for the detection of attacks. The attacks are computed based on the utilization of LSTM model for the detection and classification of attacks with use of CICIDS datasets. The comparative analysis stated that the proposed ORSS exhibits ~40% higher data transmission and ~21% reduced delay compared with state-of-techniques.
Construction mortar using Pb-Zn tailings instead of cement - less carbon emissions and better stabilisation of heavy metals
Authors: Li zhishuncheng , Ge Rui , Xu Youxiao , Qu GuangFei , Zhang Yun , Zeng Yinda , Cheng Yinhan , Wu Huanhuan
Published: July 2023

Lead-zinc tailings (LZTs) are stockpiled in large quantities and contain many heavy metals, and there is no good way to dissipate them, which seriously endangers the ecological environment and human health. In this study, we proposed a method to prepare high-strength construction mortar using LZTs (LZTs-CM) and simultaneously stabilize heavy metals in the tailings, successfully prepared an mortar with strength up to 26.288 MPa (Compressive strength greater than M25Mpa) and reduced the amount of cement by 10%. The characterization of the original tailings samples and the prepared mortar samples were analyzed by XRF, XRD, ICP-MS and other detection methods to explore the compressive strength, leaching toxicity, and hydration products of the high-strength mortar. LZTs were mixed and compounded with silica fume, fly ash and granulated blast furnace slag (GBFS) of different compositions, and the hydration reaction mechanism of the two formulations with and without tailings was investigated, as well as the stabilization effect of five heavy metals Zn2+, Cu2+, Mn2+, Cr3+ and Pb2+. The results show that the tailings in the mortar and the compound form stable heavy metal crystals through the generation of hydration products such as calcium hydroxide, as well as the ion exchange and chemical combination of hydrated C-S-H with heavy metals to achieve the solidification/stabilization of harmful substances in lead-zinc tailings with strength up to M25 standard. This study provides a new idea for the recycling of lead-zinc tailings and the harmless treatment of heavy metals in solid waste.
Motiv8: A study protocol for a cluster-randomised controlled feasibility trial of a weight management intervention for adults with severe mental illness in secure forensic services
Authors: Carney Rebekah , El-Metaal Hany , Law Heather , Savage Siobhan , Small Ingrid , hann mark , Shields Gemma , Shiers David , Carmichael-Murphy Parise , Jones Richard , Kimber Elizabeth , McDonald Andrew , Parker Sophie
Published: July 2023

Introduction
People with severe mental illness have physical comorbidities which result in significant reductions in quality of life and premature mortality. Effective interventions are required that are suitable for people in secure forensic mental health services. We conducted pilot work of a multidisciplinary weight management intervention (Motiv8) which showed improvements in physical and mental health and high levels of satisfaction. We aim to test the feasibility of Motiv8 under cluster randomised conditions, with an aim to investigate the acceptability, feasibility and potential effectiveness of this intervention to supplement standard secure care.
Methods and Analysis
A randomised waitlist-controlled feasibility trial of a lifestyle intervention (Motiv8) + TAU compared with TAU (+ Motiv8 waitlist) for adults on secure mental health units will be conducted. 32 people (4 cohorts) will be recruited from secure services in Greater Manchester Mental Health NHS Foundation Trust. Participants will be randomly allocated to Motiv8 or TAU + Motiv8 waitlist. All participants will receive Motiv8 during the trial. Assessor blinded physical/mental health and lifestyle assessments will be conducted at baseline, 10-weeks (post intervention/waitlist), and after 12 weeks (post waitlist intervention/follow up). Motiv8 is a multidisciplinary intervention including exercise sessions, cooking/nutrition classes, physical health education, psychology sessions, sleep hygiene, peer support and medication review by pharmacy. A nested qualitative study will be conducted with a subsample of participants (n = 10) to explore their experiences of taking part. Analysis will focus on feasibility outcomes and tabulated success indicators of the study (e.g., Recruitment rates, retention rates, follow-up retention and response rates, attendance at sessions, experience of involvement in the trial and delivery of intervention, assessment of safety, development of a manualised intervention). Thematic analysis will be conducted on qualitative interviews. The analysis will aim to inform the development of a definitive trial.
Ethics and Dissemination
The trial has been granted ethical approval from NHS Health Research Authority and adopted onto the UK Clinical Research Network Portfolio. Findings will be disseminated via peer-review publications, professional and public networks, conferences and clinical services.
Trial Registration Number
ISRCTN13539285
Differences in blood pressure control based on hypertension subtype in patients with a de novo diagnosis: a retrospective cohort study
Authors: Gallo-Villegas Jaime , Rivera-Martínez Wilfredo , Casanova-Valderrama María , Figueroa-Torregroza Lunevar , Ocampo-Chaparro José , Salazar-Solarte Aura , Zambrano José , Aristizabal Dagnovar
Published: July 2023

The burden of disease due to arterial hypertension (AH) is huge and studies have shown that AH prevalence continues to increase and that control rates are still low, despite public health efforts, lifestyle and pharmacological interventions recommended by guidelines. Therefore, improved therapeutic schemes based on patient´s characteristics are required to achieve blood pressure (BP) goals and thus avoid the impact AH on cardiovascular outcomes. In this real-world study, a cohort of 1397 Latin American subjects with a de novo diagnosis of AH received antihypertensive therapy following current guidelines. Thereafter, they were retrospectively classified by hypertension subtype and BP response was assessed based on whether patients initially received an appropriate treatment according to arterial hemodynamics. The initiation of a proper antihypertensive regimen was statistically significant associated with greater BP control at the follow-up clinical visit, even when the statistical model was adjusted for multiple variables (OR 2.17 CI 1.49–3.15, p value < 0.001). Among patients who were not well controlled, the divergent systolic-diastolic hypertension (SDH-D) subtype was the most frequent (46.7%), and those patients initially had higher BP, cardiac output, total systemic vascular resistance (SVR), and lower arterial compliance. Our findings indicate that the appropriate selection of an antihypertensive treatment guided by the AH subtype is associated with better BP control in patients with newly diagnosed AH.
Routing Optimization for Energy Efficiency in Software-Defined IoT and RPL Networks
Authors: Gasouma Amir , Yusof Kamaludin M. , Bouallegue Belgacem , Ahmed Abdelmoty M. , Matter Safaa S.
Published: July 2023

The Internet of Things (IoT) is a rapidly expanding network of interconnected smart devices and an active area of study in the field of information technology. These smart devices may be monitored, managed, and shared information via the internet. Some of them may be tiny gadgets or sensors with restricted power and battery life. These devices short lifespans have consequences for the IoT network due to their high energy consumption. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is defined in RFC6550 by the Internet Engineering Task Force (IETF), which is one of the most important protocols for routing for the IoT and the sole widely used protocol that aids in routing in Low Power and Lossy Networks (LLNs). Adapting objective functions (OFs) for routing and regulating control messages for RPL operations, which improves energy efficiency, is a major need in a method that handles IoT network difficulties and exploits new flexible network designs, such as Software-Defined RPL networks. This paper describes a software defined RPL system optimized for heterogeneous IoT environments. The proposed research made use of TriOF, an acronym for the three objective functions (OF1, OF2, and OF3) used for adaptive OF selection and routing. Use the Killer Whale Optimization (KWO) algorithm to select the best OF based on current network conditions. The energy efficiency of networks and OF selection adaptation both improved. The outcomes of simulations performed in Network Simulator 3 (NS3) are examined. The experiments' outcomes demonstrate the feasibility of our suggestion with reduced control overhead and control messages, as well as 40% and 60% less energy consumption when compared to previous works.
Machine Learning Uncovers CCM Isoforms as Transcription Factors
Authors: Zhang Jun , Croft Jacob , Gao Liyuan , Sheng Victor
Published: July 2023

This study investigates the TF potential of CCM gene isoforms that undergo alternative splicing and nucleocytoplasmic shuttling. Experiments showed that CCMs shuttle with progesterone receptors, which act as both cell signaling components and TFs, raises the possibility of CCMs as TFs. The study challenges existing knowledge with a Biased-SVM model to indicate that numerous CCM isoforms function as TFs.
Revealing the Potential of Necroptosis-Related Genes in Prognosis, Immune Characteristics, and Treatment Strategies for Head and Neck Squamous Cell Carcinoma
Authors: Cao Junhua , Wu Congxiao , Han Zhaofeng , Yang Zheng , Ren Minge , Wang Ximei , Liu Zheng
Published: July 2023

Necroptosis is a recently discovered apoptotic mechanism that has been linked to tumor formation, prognosis, and treatment response. However, the relationship between the TME and NRGs remains unclear. In this study, we analyzed the expression patterns of NRGs in 769 HNSCC cases from two distinct data sets. Our findings revealed distinct genetic groups and a correlation between patient clinical features, prognosis, TME cell infiltration characteristics, and NRG alterations. We then developed an NRG model to predict OS and confirmed its accuracy in predicting OS in HNSCC patients. Moreover, we have devised a precise nomogram that enhances the clinical utility of the NRG model substantially. The low-risk group had a better OS, and they were associated with immune suppression, more mutated genes, and higher TIDE scores. The risk score also had a significant correlation with the CSC index and susceptibility to anti-tumor agents. Our study provides insights into how NRGs affect prognosis, clinically significant features, TME, and immunotherapy response in HNSCC. With a better knowledge of NRGs in HNSCC, we could assess the prognosis and develop immunotherapy regimens that are more successful at opening up new doors.
The Construction and Optimization of Finished Vehicle Logistics Multimodal Transportation Routing Problem Model based on Ant Colony Algorithm under the Background of Belt and Road Initiative
Authors: Wang Yaoyan
Published: July 2023

Vehicle logistics is a very important mode of freight car combination logistics. In China, more than 80% of the total logistics operation through highway transportation is based on the completion of vehicle logistics. Because of the lack of transportation mode in the whole vehicle logistics process, the problems of the relatively small batch of transportation but large duplicate batches are very common. Therefore, in the aspect of cost control, the whole vehicle logistics system of our country has much room for improvement compared with western countries. Multimodal transportation can be adopted to reduce costs, and multimodal transport mode of vehicle logistics can also be carried out to avoid the logistics defects caused by single highway transportation, so as to facilitate management and reduce costs. The case analysis to the B Company in the entire vehicle logistics aspect work was carried out in this paper. Combined with the idea of route optimization, a model of vehicle logistics cost budget based on multimodal transportation was established. The ant colony algorithm was adopted, and the validity of the model and calculation method was verified.
Reduction in EEG Theta Power as a Potential Marker for Spatial Disorientation during Flight
Authors: Geva Gil , Getter Nir , Nakdimon Idan , Blecher Boris , Ben-Ari Oded , Gordon Barak , Shriki Oren
Published: July 2023

Spatial disorientation (SD) during flight is a common occurrence, manifesting when an aircrew's perception conflicts with the aircraft's actual motion, attitude, or position. A prevalent form of SD is the somatogyral illusion, which is elicited by constant speed rotation, causing a false perception of motion in the opposite direction once rotation ceases. This research aimed to investigate brain activity changes during exposure to this illusion. We designed a unique experimental setup where twenty-three volunteers were exposed to the somatogyral illusion while seated on a Barany (rotating) chair. The study employed EEG and eye-tracking glasses to monitor brain activity and eye movements, respectively. Subjects were isolated from external stimuli, promoting effective illusion induction. Participants reported their perceived motion direction using a joystick, allowing us to compare a reference condition to one with the illusion present. Results indicated a significant decrease (52%) in theta power (4–8 Hz) over left frontal channels during the illusion, complemented by the occurrence of nystagmus in 72% of trials. These findings align with previous studies linking SD and theta band changes, suggesting implications for EEG-based identification of SD in flight.
Crack The Crux Of "Psychological Contract" Between Sports And Students Under Big Data Technology
Authors: Chen Wenfeng
Published: July 2023

Studies on the elements that impact students' learning in sports education are important because they reflect the shift in focus from teachers to students brought about by educational reform and growth. This research investigates how the actions of college and university sports instructors affect their students' drive to learn and study. This paper develops a behavioral model of the psychological contract between Chinese undergraduate students and their physical education instructors. We first collect the student data from numerous firms to begin this inquiry. Before processing a raw dataset, min-max normalization must be carried out. The psychological contract scale served as the basis for the survey instrument created for use with college faculty and students. "Statistical analysis is done using the Student t-test, Chi-square test, and Analysis of Variance (ANOVA)." According to the findings, the psychological agreement between a teacher and their pupils has a major influence on the latter's actions in the classroom. Students’ learning motivation acts as mediator between instructors' teaching practices and students’ achievement. Improved communication between faculty and undergraduates in physical education classes, more teacher motivation to effectively administer the physical education curriculum, and higher standards for physical education instruction are all tangible outcomes of this research.
Study on Ensemble Calibration of Flood Forecasting Based on Response curve of rainfall dynamic system and LSTM.
Authors: Tian Lu , Li Zhichao , Liu Chengshuai , Yu Qiying , Li Wenzhong , Hu Caihong
Published: July 2023

A dynamic system response curve correction method is used to establish the error of the rainfall time series, modify the surface precipitation of the basin, and use the surface precipitation of the revised as input to improve flood forecast accuracy using the Shouxi watershed in Sichuan Province and the Qingyangcha domain in Shanxi Province as the research object. Flood forecasting is carried out using the excess storage and excess infiltration simultaneously model. Combined with the hierarchical optimization method and the LSTM (Long Short-Term Memory neural network) error output correction method, the three-process error set correction is carried out. The results show that the accuracy of the flood forecast discharge with area-rainfall correction was improved compared with that without area-rainfall correction. Specifically, The absolute value of flood peak error for 12 of 15 floods in the Shouxi Basin validation set decreased by 0.566.3% compared to before the areal rainfall correction, the NSE of 13 flood forecast discharge increased by 0.0020.015, and the current difference of 2 peaks shortened by 1 hour. The peak error of five floods was reduced by 0.23-5.49% in the Qingyangcha watershed validation set compared to before the areal rainfall correction, the NSE (Nash Social Welfare Efficiency) of five flood forecast flows was increased by 0.01-0.071, and the current difference of two peaks was shortened by one hour. The comprehensive results show that this method is applicable to reduce the prediction error and improve the accuracy of flood forecasting in the watershed.
Benthic daily oxygen variability and stress as drivers for animal diversification in the Cambrian
Authors: Hammarlund Emma , Bukkuri Anuraag , Norling Magnus , Posth Nicole , Carroll Christopher , Baratchart Etienne , Amend Sarah , Gatenby Robert , Pienta Kenneth , Brown Joel , Peters Shanan , Hancke Kasper
Published: July 2023

The delay between the origin of animals in the Neoproterozoic and their Cambrian diversification remains perplexing. Animal diversification mirrors an expansion in marine shelf area, but the mechanisms linking this environmental change to early organismal ecology are unclear. In this study, we used a biogeochemical model to consider oxygen dynamics at the sunlit sediment–water interface over night-day (diel) cycles in the early Cambrian under a greenhouse climate. We found that temperatures dictated the diurnal benthic oxic-anoxic shifts that were physiologically stressful to early animals and this dynamic expanded over nutrient-rich shelf areas as continents were flooded in the Cambrian. We suggest that the combination of a greenhouse climate and continental flooding combined to amplify diurnal benthic redox variability, which promoted the adaptive radiation of animals tolerant to oxygen fluctuations and stress, the Metazoa.
Enhancing Mechanical Properties of PLA and PP Composites through Ionic Zeolite with copper nanoparticles Reinforcement: Microstructural and Micromechanical Characterization
Authors: Onate Angelo , Sáez-Llanos Thyare , Jaramillo Andrés , Vargas-Silva Gustavo , Melendrez Manuel , Medina Carlos
Published: July 2023

The objective of this research is the micromechanical characterization of new materials for 3D printing, comprised of commercial polymer matrices of PLA and PP, reinforced with zeolite and copper nanoparticles. To characterize the microstructure of the composite materials, digital tools such as ImageJ software were used to determine the number and size of inclusions present in the samples through image analysis. Besides, the morphology of the reinforcing phase was determined through analysis with the SEM microscope. To determine the mechanical properties of the composite materials, nanoindentation was used to obtain the elastic modulus and Poissons ratio of constituents. With both, microstructure characterization and mechanical properties of the constituents, the composite materials obtained were simulated using Digimat FE software, and mentioned engineering constants were obtained. Finally, simulations results were compared with experimental tensile testing of studied composite materials, and it was determined that the simulation using Digimat delivered reliable mechanical results.
Exploring research trend and hotspots on oxidative stress in ischemic stroke (2001-2022): insights from bibliometric
Authors: Jiang Nan , Yang Ting , Han Hongxia , Shui Jing , Hou Miaomiao , Wei Wenyue , Kumar Gajendra , Song Lijuan , Ma Cungen , Li Xinyi , Ding Zhibin
Published: July 2023

Oxidative stress is widely involved in the pathological process of ischemic stroke and ischemia-reperfusion. Several research have demonstrated that eliminating or reducing oxidative stress can alleviate the pathological changes of ischemic stroke. However, current clinical antioxidant treatment did not always perform as expected. This bibliometric research aims to identify research trends, topics, hotspots and evolution on oxidative stress in the field of ischemic stroke, and to find potentially antioxidant strategies in future clinical treatment. Relevant publications were searched from the Web of Science (WOS) Core Collection databases (2001–2022). VOSviewer was used to visualize and analyze the development trends and hotspots. In the field of oxidative stress and ischemic stroke, the number of publications increased significantly from 2001 to 2022. China and the USA were the leading countries for publication output. The most prolific institutions were Stanford University. Journal of Cerebral Blood Flow and Metabolism and Stroke were the most cited journals. The research topics in this field include inflammation with oxidative stress, mitochondrial damage with oxidative stress, oxidative stress in reperfusion injury, oxidative stress in cognitive impairment and basic research and clinical translation of oxidative stress. Moreover, "NLRP3 inflammasome", "autophagy", "mitophagy", "miRNA", "ferroptosis" and "signaling pathway" are the emerging research hotspots in recent years. At present, multi-target regulation focusing on multi-mechanism crosstalk has progressed across this period, while challenges come from the transformation of basic research to clinical application. New detection technology and new nanomaterials are expected to integrate oxidative stress into the clinical treatment of ischemic stroke better.
Investigating the antimicrobial activity of cell-free supernatant of lactic acid bacteria against spoilage bacteria of vacuum-packed sliced emulsion-type sausages
Authors: Tajbakhsh Samaneh , Eskandari Mohammad Hadi , Shekarforoush Seyed Shahram
Published: July 2023

Spoilage is very common in vacuum-packed sliced emulsion-type sausages during refrigerated storage. Bacteria causing spoilage of this products were identified. Four lactic acid bacteria (LAB) were the predominant spoilage bacteria. A total of 43 LABs were screened for inhibitory activity against the four spoilage bacteria. Six strains of Lactobacillus acidophilus ATCC 4356, Lactobacillus helveticus PTCC 1332, Lactiplantibacillus plantarum CEC 17484, Lactiplantibacillus plantarum LL441, Lacticaseibacillus rhamnosus GG ATCC 53103, and Pediococcus acidilactici DSM 20284 that produced antimicrobial metabolites effective against these spoilage agents, including compounds with a proteinaceous nature, in addition to acids and H2O2, were selected as protective bacteria. The cell-free supernatant (CFS) of the protective bacteria successfully inhibited four spoilage bacteria (more than 88%). The MIC90 of all protective bacteria was less than 10 mg/ml against E. mandetii and L. sakei. The CFS of L. rhamnosus had an effect on three spoilage bacteria, including L. sakei, E. mandetii, and L. curvatus, at the lowest concentration (3.0, 3.1, and 10.5 mg/ml, respectively). The effective metabolites were resistant to the pasteurization temperature of sausage, so these supernatants can be used even in the pre-pasteurization stage of the production of sliced sausage as biopreservatives.
Properties of -1 and 1 being Roots of Polynomials over Real/Complex Field
Authors: Bhosale Mandar
Published: July 2023

The given article is about elaborating the alternate proofs for 1 and -1 being roots of polynomials having some specific properties. The proof explains equivalent conditions with more explanation. The first proposition states that for any polynomial of single variable 𝑥 say 𝑝(𝑥), the sum of all coefficients is zero if and only if (𝑥 − 1) is factor of 𝑝(𝑥) equivalently 1 is root of 𝑝(𝑥).
The second Proposition states for any polynomial of single variable 𝑥 say 𝑝(𝑥), alternate sums of coefficients i.e. sum of coefficients of odd degree terms (𝑥, 𝑥3, 𝑥5, .., 𝑥2𝑛−1, ..) and sum of coefficients of even degree terms (constant, 𝑥2, 𝑥4, .., 𝑥2𝑛 , ..) are same if and only if (𝑥 + 1) is a factor of 𝑝(𝑥) equivalently -1 is the root of 𝑝(𝑥).
As mentioned above, the arguments are equivalent conditions hence we are proving by proving two parts i.e. prove if 𝑝 is true then 𝑞 is true. After this,we will prove the converse part i.e. if 𝑞 is true then 𝑝 is true. Both parts will be done using the direct proof method.
Improved Corrosion Resistance and Cytotoxicity of Nickel-based alloy using Novel Plasma processing technique
Authors: Yousaf Muhammad , Iqbal Tahir , Mansha Muhammad Salim , Saeed Adnan , Abrar Muhammad , Afsheen Sumera , Ahmed Irfan , AlObaid Abeer A. , Al-Maswari Basheer M.
Published: July 2023

Nickel-based (NiCr) alloys are mostly utilized in the dental industry because of their good corrosion resistance, ease of casting, and adequate thermal coefficient of friction with ceramic porcelain. However, leakage of toxic metal ions (Ni and Cr) due to breakage or damage of protective metal oxide layers in aggressive body fluids affects corrosion resistance, tribological properties, and cytotoxicity. These drawbacks ultimately affect the biocompatibility of NiCr alloys for medical applications. This study employs magnetron sputtering in conjunction with cathodic cage plasma nitriding (CCPN) to perform a novel duplex plasma treatment on Ni-Cr alloy. Moreover, the cathodic cage plasma-treated TiN (CCPN-TiN) samples showed further enhanced corrosion resistance and low metal ion leakage. These findings made duplex plasma treatment an efficient method for the surface modification of metallic alloys against the leaching of toxic ions in chloride-aggressive electrolytes, thus proving an excellent strategy for various biomedical applications.
Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems
Authors: Chen Hao-Yuan , Chang Yen-Jui , Chang Ching-Ray
Published: July 2023

Quantum computing holds great potential for advancing the limitations of machine learning algorithms to handle higher data dimensions and reduce overall training parameters in deep neural network (DNN) models. This study uses a parameterized quantum circuit (PQC) on a gate-based quantum computer to investigate the potential for quantum advantage in a model-free reinforcement learning problem. Through a comprehensive investigation and evaluation of the current model and capabilities of quantum computers, we designed and trained a novel hybrid quantum neural network based on the latest Qiskit and PyTorch framework. We compared its performance with a full-classical DNN with and without an integrated PQC. Our research provides insights into the potential of deep quantum learning to solve a maze problem and, potentially, other reinforcement learning problems. We conclude that various reinforcement learning problems can be effective with reasonable training epochs. Moreover, a comparative discussion of the various quantum reinforcement learning model on maze problems is discussed to evaluate our research's overall potential and advantages.
Epidemiology of Ischemic Stroke and Hemorrhagic Stroke in Venoarterial Extracorporeal Membrane Oxygenation
Authors: Hwang Jaeho , Kalra Andrew , Shou Benjamin L , Whitman Glenn , Wilcox Christopher , Brodie Daniel , Zaaqoq Akram M , Lorusso Roberto , Uchino Ken , Cho Sung-Min
Published: July 2023

Background
While venoarterial extracorporeal membrane oxygenation (VA-ECMO) provides lifesaving support for cardiopulmonary failure, complications may arise that increase mortality, with few studies focusing on ischemic/hemorrhagic stroke. We aimed to determine the trends of stroke incidence and mortality, associations with each other, and associations with total case volume at each Extracorporeal Life Support Organization (ELSO) center.
Methods
Retrospective analysis of ELSO registry, including adult VA-ECMO patients from 534 international centers between 2012–2021, excluding extracorporeal cardiopulmonary resuscitation. Cochran-Armitage test and Poisson regression were used for trend analysis of stroke incidence and mortality. Kaplan-Meier curves, hazard functions, and multivariable logistic regression were used to study the impact of stroke on 90-day mortality.
Results
Of 33,041 patients (median age = 58 years, female = 32%), 4% developed ischemic stroke, and 2% developed hemorrhagic stroke. Ischemic stroke incidence increased (×1.21/year, p < 0.0001), while hemorrhagic stroke incidence remained stable, and overall 90-day mortality declined (1.78%/year, p < 0.0001). Ischemic/hemorrhagic strokes were associated with increased overall 90-day mortality (OR = 3.29, 3.99 respectively, both p < 0.0001) after controlling for pre-selected covariates, including age, pre/post-cannulation lab values, ECMO duration, center volume, and on-ECMO complications. Total center volume was associated positively with ischemic/hemorrhagic stroke incidences (OR = 1.039, 1.053 per-additional-100-cases respectively, both p = 0.022), but inversely with 90-day mortality (OR = 0.909 per-additional-100-cases, p < 0.0001). Hazard of death was highest in the first several days of VA-ECMO.
Conclusion
In VA-ECMO patients, while the reported ischemic stroke incidence steadily increased over time, 90-day mortality decreased. ELSO centers with higher case volumes reported greater stroke incidence, but lower mortality. Both ischemic/hemorrhagic strokes were associated with increased mortality.
Empowering 5G mmWave: Leveraging KML Placemarks for Enhanced RF Design and Deployment Efficiency
Authors: Fernandez Gustavo A
Published: July 2023

This publication explores the significance of Keyhole Markup Language (KML) in telecommunications, particularly in the context of 5G mmWave RF design and planning. With the advent of 5G mmWave technology, the demand for seamless and efficient network deployments has never been greater.The deployment of small cells and repeaters for 5G mmWave necessitates utmost precision in location accuracy and rapid information exchange during site surveys and evaluations. The challenges of mmWave frequencies, including their limited range and susceptibility to attenuation, intensify the complexity and criticality of this process. Network operators must ensure that the chosen location is devoid of obstacles to enable optimal signal propagation and service provision. Identifying an ideal location to deploy mmWave small cells and repeaters is imperative to achieve seamless and reliable service coverage, making efficient spatial data handling all the more vital in 5G mmWave RF design.KML is a standard format for expressing geographic data, providing an intuitive representation of location-based information. This paper introduces an application that harnesses KML's capabilities to simplify the conversion of KML files into user-friendly HTML tables. The app streamlines the process of extracting placemark coordinates from Google Earth, enabling quick and efficient organization into tables for easy integration into other platforms. This tool proves highly valuable for professionals frequently using Google Earth, as it enhances documentation efficiency, supports the reduction of deployment time, and boosts overall work performance. By leveraging KML placemarks, professionals gain valuable insights, enabling them to make informed decisions and help them quickly identify and overcome challenges in network deployment. With this tool, researchers and engineers can successfully navigate the complexities of 5G mmWave deployments by simplifying spatial data handling and promoting effective collaboration and site survey feedback utilization.
Survey of load frequency control strategies in a Microgrid
Authors: DEFFO BORIS ARNAUD NOTCHUM , Bakouri Anass
Published: July 2023

Microgrids (MGs) represent a set of interconnected power generation sources, storage devices, and loads. The most solicited sources are renewable energy sources (RESs) because they help fight against global warming. However, the intermittency of the photovoltaic (PV) and wind (WTG) sources that are the most used will increase the power imbalance that generates the frequency variations since the inertia in the MGs is low. Thus, control strategies are increasingly used to ensure automatically a frequency balance. Therefore, in this paper, after presenting the microgrid and its components understandably, we have used recent papers to illustrate and discuss the most important frequency control strategies within a microgrid, and also some perspectives for future research to better exploit microgrids are presented.
Unveiling Plant Species Richness Patterns and Climate Influences in Indian Biogeographic Zones
Authors: Tripathi Poonam , Behera Mukunda D , Roy Partha Sarathi
Published: July 2023

Introduction
Conservation efforts have traditionally focused on biodiversity hotspots, overlooking the essential ecological roles and ecosystem services provided by cold spots. Cold spots are areas outside biodiversity hotspots, characterized by low species diversity and harboring rare species living in threatened habitats.
Aim
This study aims to predict the present and future plant species distribution in cold spots across India, considering various environmental and non-environmental variables.
Location
India
Methods
The Indian national-level plant species database generated through the project ‘Biodiversity Characterization at Landscape Level’ was used. The species modelling (70% randomly selected training data) was carried out for four major biogeographic zones of India namely Arid and semi-arid zone, Deccan peninsula, and Gangetic plain. Generalized Linear Model (GLM), Generalized Boosted Model (GBM), Random Forest (RF), Support Vector Machine (SVM), and ensemble modeling were compared to predict species distribution. Future representative concentration pathways (RCP4.5 & RCP8.6) were used to forecast species distribution.
Results
The study demonstrated good predictive ability with water and energy variables dominating in all zones, showing a strong agreement with the observed data (30% subset of the original data). Temperature annual range, annual precipitation, and precipitation of the driest month (bio7, bio12, and bio14) significantly influenced (r > 0.4) plant species patterns in the arid and semi-arid zone. Ensemble modeling showed improved results when validated with observed data, exhibiting a significant reduction in the RMSE and an improved correlation (r=0.8). Non-environmental variables (elevation and human influence index) showed significant influence in combination with water and energy variables in the Deccan peninsula zone.
We observed continuous species loss in both future climate scenarios. Among biogeographic zones, the semi-arid and arid zones showed the maximum probable increase in species, with 69% and 52.5% of grids gaining species in 2050 (RCP4.5) and 69% and 84.7% of grids gaining species in 2070 (RCP8.6) respectively.
Conclusion
The study provides insights into the species richness distribution of cold spots in major Indian biogeographic zones, supporting their climate-derived patterns at a macro-scale. Ensemble modeling proves to be more accurate than individual models, emphasizing its potential for conservation efforts. The study calls for a performance-based conservation approach, prioritizing criteria to safeguard valuable ecosystems and prevent species loss.
Visual speech cues enhance neural speech tracking in right auditory cluster leading to improvement in speech in noise comprehension in older adults with hearing impairment
Authors: Frei Vanessa , Schmitt Raffael , Meyer Martin , Giroud Nathalie
Published: July 2023

Comprehending speech in noisy situations is difficult and suffers with aging, hearing loss, and cognitive decline. Using visual speech cues improves perception and comprehension of speech in noise (SiN) in older adults with hearing impairment. In the current study, we investigated neurofunctional correlates (i.e., neural tracking of speech) of the visual enhancement effect in a naturalistic setting while older adults with hearing impairment (N = 67) listened to sentences in babble noise in audio-only and audiovisual conditions and performed an intelligibility and a comprehension task, while electroencephalography (EEG) was recorded. Behaviourally, we found that visual speech cues improved intelligibility and comprehension of speech presented in babble noise and individuals with higher working memory capacity benefitted. Furthermore, we found that the visual enhancement effect was accompanied by increased cortical tracking of the speech envelope. A post hoc analysis revealed that individuals who were low performers in the audio-only condition (i.e., < 70% correct) improved in speech in noise comprehension in an audiovisual setting. Further, these low auditory-only performers showed deficient neural speech tracking in a right-hemispheric temporo-parieto-occipital, which improved significantly when visual speech cues were presented leading to more bilateral processing of speech. Overall, our results show that older adults with hearing impairment who have difficulties with speech in noise perception use visual speech cues to improve performance, which is reflected in more bilateral processing of speech.
Reconstruction of the Frontal Aslant Tract (FAT) in patients with different types of frontal lobe tumors, considering diverse methods of delineation
Authors: Kierońska-Siwak Sara , Jabłońska Magdalena , Sokal Paweł
Published: July 2023

The Frontal Aslant Tract (FAT) is a bundle of nerve fibers located in the brain that connects the frontal lobe to the pars aslant of Broca's area. It serves as a crucial neural pathway involved in language regulation, speech, and motor control. The FAT is part of the broader cingulo-fronto-parietal network, facilitating communication between the frontal and posterior regions of the brain. The objective of this study is to investigate the connectivity of the Frontal Aslant Tract using diffusion tensor imaging-based fiber tractography analysis. We compared the fiber count, tract length, shape, and projections of the FAT in patients with frontal tumors to a control group. Among patients diagnosed with brain tumors, we observed a reduction in the number of nerve fibers within the FAT and a decrease in pathway volume. When delineating the FAT using ROIs encompassing the superior frontal gyrus and endpoint in the pars opercularis of the inferior frontal gyrus, we obtained the highest fiber count. The specific anatomy of the FAT is heavily influenced by the choice of ROI and endpoint. Accurate identification of the FAT in patients with frontal lobe tumors is crucial to prevent postoperative aphasia.
Probing Berry phase effect in topological surface states
Authors: Bai Ya , Jiang Yang , Zheng Wenyang , Chen Jiayin , Wang Shuo , Liu Candong , Li Ruxin , Liu Peng
Published: July 2023

Berry phase and topology of the Bloch wavefunction, originating from the interplay of internal quantum attributes of crystal electrons1, holds great significance in classifying novel quantum phases2,3 and endowing emergent functions4. In quantum materials with broken time-reversal or spatial-inversion symmetry, Bloch electrons in motion necessarily carry a geometric phase, and define the topological states2,3,5 and various quantum and nonlinear Hall effects6,7. Recent advances in light-wave-driven optical harmonic emission enable the observation of the rapid evolution of Bloch electrons on a subcycle time scale 8-13 and empower the harnessing of electron dynamics associated with Berry phase effects14,15. However, the correlation between subcycle electron motion and the accumulation of the quantum phase in geometric aspects of the evolving Bloch waves has not been observed. Here, we demonstrate that the Berry phase can be measured and manipulated in topological surface states using two-colour high-harmonic spectroscopy16. This is achieved by introducing a weak second harmonic field with a precisely controlled time delay to perturb the phase evolution of Dirac fermions and thus provide access to the Berry phase. Furthermore, we observe an overwhelming Berry phase effect that deforms quantum pathways of electron-hole pairs. Our observation demonstrates the ability to harness the electron spin using lightwaves in quantum materials with strong spin-orbit interaction, in addition, enhances the application of light-wave-driven spintronics and topological electronics.
Better Together: Volatile-mediated Interguild Effects on the Preference of Tuta Absoluta and Trialeurodes Vaporariorum for Tomato Plants
Authors: RODRIGO Federico , BURGUEÑO Anna P. , González Andrés , ROSSINI Carmen
Published: July 2023

Plant-herbivore interactions have been extensively studied in tomato plants and their most common pests. Tomato plant chemical defenses, both constitutive and inducible, play a role in mediating these interactions. Damaged tomato plants alter their volatile profiles, affecting herbivore preferences between undamaged and damaged plants. However, previous studies on tomato volatiles and herbivore preferences have yielded conflicting results, both in the volatile chemistry itself as well as in the attraction/repellent herbivore response. This study revisits the volatile-mediated interactions between tomato plants and two of their main herbivores: the leafminerTuta absolutaand the whiteflyTrialeurodes vaporariorum. Tomato plant volatiles were analyzed before and after damage by each of these herbivores, and the preference for oviposition (T. absoluta) and settling (T. vaporariorum) on undamaged and damaged plants was assessed both after conspecific and heterospecific damage. We found that both insects consistently preferred damaged plants over undamaged plants. The emission of herbivore-induced plant volatiles (HIPVs) increased afterT. absolutadamage but decreased afterT. vaporariorumdamage. While some of our findings are in line with previous reports,T. absolutapreferred to oviposit on plants damaged by conspecifics, which differs from earlier studies. A comparison of HIPVs emitted after damage byT. absolutaandT. vaporariorumrevealed differences in up- or down-regulation, as well as significant variations in specific compounds (12 forT. absolutaand 26 forT. vaporariorumdamaged-plants). Only two compounds,E-caryophyllene and tetradecane, significantly varied because of damage by either herbivore, in line with the overall variation of the HIPV blend. Differences in HIPVs and herbivore preferences may be attributed to the distinct feeding habits of both herbivores, which activate different defensive pathways in plants. The plant's challenge in simultaneously activating both defensive pathways may explain the preference for heterospecific damaged plants found in this study, which are also in line with our own observations in greenhouses.
Argumentation-Based Multi-Agent Distributed Reasoning in Dynamic and Open Environments
Authors: Monte-Alto Helio , Morveli-Espinoza Mariela , Tacla Cesar
Published: July 2023

This work presents an approach for distributed and contextualized reasoning in multi-agent systems, considering environments in which agents may have incomplete, uncertain and inconsistent knowledge. Knowledge is represented by defeasible logic with mapping rules, which model the capability of agents to acquire knowledge from other agents during reasoning. Based on such knowledge representation, it is proposed an argumentation-based reasoning model that enables distributed building of reusable argument structures to support conclusions. Conflicts between arguments are resolved by an argument strength calculation that considers the trust among agents and the degree of similarity between knowledge of different agents, based on the intuition that greater similarity between knowledge defined by different agents implies in less uncertainty about the validity of the built argument. Contextualized reasoning is supported through sharing of relevant knowledge by an agent when issuing queries to other agents, which enable the cooperating agents to be aware of knowledge not known a priori but that is important to reach a reasonable conclusion given the context of the agent that issued the query. A distributed algorithm is presented and analytically and experimentally evaluated asserting its computational feasibility. Finally, our approach is compared to related work, highlighting the contributions presented, demonstrating its applicability in a broader range of scenarios, and presenting perspectives for future work.