bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Passive Social Media Viewers in Influence Maximization
Authors: Kahr Michael , Leitner Markus , Ljubić Ivana
Published: March 2024

A frequently studied problem in the context of digital marketing for online social networks is the influence maximization problem that seeks for an initial seed set of influencers to trigger an information propagation cascade (in terms of active message forwarders) of expected maximum impact. Previously studied problems typically neglect that the probability that individuals passively view content without forwarding it is much higher than the probability that they forward content. Considering passive viewing enables us to maximize more natural (social media) marketing metrics, including (a) the expected organic reach, (b) the expected number of total impressions, or (c) the expected patronage, all of which are investigated in this paper for the first time in the context of influence maximization. We propose mathematical models to maximize these objectives, whereby the model for variant (c) includes individual’s resistances and uses a multinomial logit model to model customer behavior. We also show that these models can be easily adapted to a competitive setting in which the seed set of a competitor is known. In a computational study based on network graphs from Twitter (now X) and from the literature, we show that one can increase the expected patronage, organic reach, and number of total impressions by 36% on average (and up to 13 times in particular cases) compared with seed sets obtained from the classical maximization of message-forwarding users.

History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete.

Funding: This work was supported by the Federal Ministry of Education, Science and Research of Austria and by the Austrian Agency for International Mobility and Cooperation in Education, Science and Research [Reference ICM-2019-13384].

Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0047 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0047 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
Computing Bipath Multicommodity Flows with Constraint Programming–Based Branch-and-Price-and-Cut
Authors: Zhang Jiachen , Magnouche Youcef , Bauguion Pierre , Martin Sebastien , Beck J. Christopher
Published: March 2024

We propose a constraint programming (CP)–based branch-and-price-and-cut framework to exactly solve bipath multicommodity flow (MCF): an MCF problem with two paths for each demand. The goal is to route demands in a capacitated network under the minimum cost. The two paths must have disjoint arcs, and the delays accumulated along the two paths must be within a small deviation of each other. CP is used at multiple points in this framework: for solving pricing problems, for cut generation, and for primal and branching node heuristics. These modules use a CP solver designed for network routing problems and can be adapted to other combinatorial optimization problems. We also develop a novel, complete, two-level branching scheme. On a set of diverse bipath MCF instances, experimental results show that our algorithm significantly outperforms monolithic CP and mixed integer linear programming models and demonstrate the efficiency and flexibility brought by the tailored integration of linear programming and CP methodologies.

History: Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis.

Funding: This work was supported by the Natural Sciences and Engineering Research Council of Canada; Huawei Technologies.

Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0128 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0128 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
Amazon Locker Capacity Management
Authors: Sethuraman Samyukta , Bansal Ankur , Mardan Setareh , Resende Mauricio G. C. , Jacobs Timothy L.
Published: March 2024

Amazon Locker is a self-service delivery or pickup location where customers can pick up packages and drop off returns. A basic first-come-first-served policy for accepting package delivery requests to lockers results in lockers becoming full with standard shipping speed (3- to 5-day shipping) packages, leaving no space for expedited packages, which are mostly next-day or two-day shipping. This paper proposes a solution to the problem of determining how much locker capacity to reserve for different ship-option packages. Yield management is a much-researched field with popular applications in the airline, car rental, and hotel industries. However, Amazon Locker poses a unique challenge in this field because the number of days a package will wait in a locker (package dwell time) is, in general, unknown. The proposed solution combines machine learning techniques to predict locker demand and package dwell time with linear programming to maximize throughput in lockers. The decision variables from this optimization provide optimal capacity reservation values for different ship options. This resulted in a year-over-year increase of 9% in Locker throughput worldwide during the holiday season of 2018, impacting millions of customers.

History: This paper was refereed.
Lung underdevelopment: case reports and a literature review
Authors: Al-Tarbsheh Ali , Halaseh Ramez , Williams Veronica , Schultz Kaila , Martinez Nydia
Published: March 2024

Lung underdevelopment is a rare congenital anomaly with variable clinical significance and presenting symptoms. It usually manifests during childhood. We present two cases of developmental lung anomaly subtypes and discuss clinical presentation and outcomes in such patient populations.
Dynamic Investigation of Auxin on Germination of Sesamum Indicum Seed by 1H Spectroscopy and Chemical Shift Selection Imaging
Authors:   Department of Physics, School of Science, Jimei University, Xiamen, Fujian Province, China, Xiao Yuhui ,   Department of Marine Engineering, School of Marine Engineering, Jimei University, Xiamen, Fujian Province, China, Liao Wenliang ,   Department of Physics, School of Science, Jimei University, Xiamen, Fujian Province, China, Cai Honghao ,   Department of Physics, School of Science, Jimei University, Xiamen, Fujian Province, China, Ni Hui ,   College of Food and Biology Engineering, Jimei University, Xiamen, Fujian Province, China,   Fujian Provincial Key Laboratory of Food Microbiology and Enzyme Engineering, Xiamen, Fujian Province, China
Published: March 2024

Ger mination of sesame seeds in acidic and indole-3-acetic acid (IAA) liquid mediums was investigated using single pulse 1H spectroscopy and chemical shift selection imaging. The spectra and images demonstrated high correlation and reliability. Chemical shift selection imaging allowed for an intuitive comprehension of the dynamic distribution of metabolites and structural changes during germination, leading to a clearer understanding of IAA’s regulation on sesame metabolites, when combined with 1H spectra. Results showed that exogenous hormones accelerated the decomposition of lipid macromolecules before rapid radicle growth, while IAA delayed sesame development at this stage. However, post-growth delay, the addition of IAA effectively accelerated germination. This study confirms that 1H spectroscopy and chemical shift selection imaging can interpret the metabolic response of plants to the change in their internal physiological state and help to determine the optimal time to add IAA.
Advancements in Deep-Learning-Based Object Detection in Challenging Environments
Authors: Mukhopadhyay Abhishek , Biswas Pradipta
Published: March 2024

This article focuses on object detection in challenging environments, where objects of interest need to be detected in images captured under unconstrained conditions. These environments can include outdoor scenes with varying lighting, weather conditions, and background clutter. Object detection in such scenarios is crucial for applications like autonomous driving, surveillance, and industrial production inspection. The paper explores existing techniques for object detection in challenging environments and proposes novel solutions to enhance its performance. One key aspect emphasized in the paper is the need for relevant datasets to validate models under unconstrained scenarios. While several datasets already exist, the research identifies gaps in specific situations and addresses them by proposing new datasets, such as the Indian Lane Dataset for autonomous vehicles. The proposed object detection framework leverages spatial information to detect objects in challenging environments, and its performance is evaluated against benchmark datasets and the newly proposed datasets. A real-world application demonstrates significant improvements in object detection performance in natural environments.
Adversarial Machine-Learning-Enabled Anonymization of OpenWiFi Data
Authors: Kuili Samhita , Dabbour Kareem , Hasan Irtiza , Herscovich Andrea , Kantarci Burak , Chenier Marcel , Erol-Kantarci Melike
Published: March 2024

Data privacy and protection through anonymization is a critical issue for network operators or data owners before it is forwarded for other possible use of data. With the adoption of Artificial Intelligence (AI), data anonymization augments the likelihood of covering up necessary sensitive information; preventing data leakage and information loss. OpenWiFi networks are vulnerable to any adversary who is trying to gain access or knowledge on traffic regardless of the knowledge possessed by data owners. The odds for discovery of actual traffic information is addressed by applied conditional tabular generative adversarial network (CTGAN). CTGAN yields synthetic data; which disguises as actual data but fostering hidden acute information of actual data. In this paper, the similarity assessment of synthetic with actual data is showcased in terms of clustering algorithms followed by a comparison of performance for unsupervised cluster validation metrics. A well-known algorithm, K-means outperforms other algorithms in terms of similarity assessment of synthetic data over real data while achieving nearest scores 0.634, 23714.57, and 0.598 as Silhouette, Calinski and Harabasz and Davies Bouldin metric respectively. On exploiting a comparative analysis in validation scores among several algorithms, K-means forms the epitome of unsupervised clustering algorithms ensuring explicit usage of synthetic data at the same time a replacement for real data. Hence, the experimental results aim to show the viability of using CTGAN-generated synthetic data in lieu of publishing anonymized data to be utilized in various applications.
Reward Based Garbage Monitoring and Collection System Using Sensors
Authors: Aggarwal Deepti , Mittal Sonu , Upreti Kamal , Nayak Pinki
Published: March 2024

Most of the time in our surroundings we come across the overfilled garbage bins near the lakes. When the bins are full, people just throw the waste here and there, which eventually goes into the lakes and pollutes the water bodies. This is because of improper dumping of garbage that is practiced in our society. With the increase in population, this problem is taking really bad shape. The prime need is to maintain a clean and healthy environment with proper disposal of waste. This paper presents a small effort to reduce this garbage problem. An Android app has been created which keeps on checking whether the dustbin is full. Also, the people will be rewarded for throwing waste into the dustbins. A QR code has been attached to the dustbin which will be scanned for rewarding the people. The dustbins use an IR sensor that detects the receiver of waste in bins. Major part of this proposed system includes the proper working of mobile application and proximity sensors. Arduino is used to maintain the proper connection with sensors and application and that is done by Bluetooth sensor. The main objective of this proposed system is to lure people to put waste into the dustbin along with the contribution towards smart city vision. This paper also gives a brief overview of the technologies and work done so far in this field.
Enhancing Gesture-Controlled Virtual Mouse and Virtual Keyboard Using AI Techniques
Authors: Kotti Jayasri , Padmaja B. , Deepa D.
Published: March 2024

Artificial Intelligence has become an essential part of modern technology. Although computer technology is advanced, it can still be improved to make it more user-friendly. One way to do this is to replace touchscreen desktops with a virtual mouse and keyboard. This can reduce the need for gadgets and enhance human-computer interaction. During the COVID-19 pandemic, reducing human intervention and dependency on devices has been critical in controlling the spread of the virus. This is where a battery-powered or Bluetooth mouse, powered by virtual reality technology, can be helpful. The virtual mouse is created using OpenCV and virtual reality technology, with the proposed system utilizing advanced tools such as MediaPipe and Python. The MediaPipe library is particularly useful in artificial intelligence projects, as it enhances the efficiency of the model. The system is an AI-based mouse and keyboard that can be controlled using hand gestures. The user interacts with the system through the camera output displayed on the screen, while the webcam serves as an input device. Python and OpenCV tools are used for implementation, making it applicable in pandemic situations and smart teaching systems. The proposed system works on Enhancing gesture Controlled Virtual Mouse and Virtual Keyboard through Virtual Assistant using AI Techniques.
Nanohybridization Effects on Impact Behavior of Basalt/Glass Fiber Reinforced Epoxy Hybrid Nanocomposites
Authors: V. Boobalan  , T. Sathish
Published: March 2024

Basalt fiber-based composites have received greater attention from manufacturers and researchers recently for use in a variety of structural applications, owing to their high strength-to-weight ratio, high stiffness, and excellent mechanical properties. The main objective of the current research is to examine the impact behavior of hybrid basalt/glass fiber reinforced composites that have been altered by the addition of MWCNTs and SiO2 (Nano silica) to the epoxy matrix as per the ASTM standards. All of the composites were created using Manual lay-up method followed by Compression molding using novel symmetric stacking sequence configurations of B/GG/BB/GG/BB/GG/B fibers with nanoparticles at weight percentages of 0%, 1% (0.5% MWCNTs + 0.5% SiO2) 2% (1% MWCNTs + 1% SiO2) and 3% (1.5 % MWCNTs + 1.5% SiO2). The homogeneous dispersion of nanoparticles in the epoxy matrix was achieved by ultrasonicator and magnetic stirrers. The maximum value of Izod impact strength was recorded as 203 kJ/m2 for the composite filled with 2 wt. % of nano-fillers. In comparison to the composite containing no fillers, the composite adding 2 wt. % showed a 24% improvement from 167 to 203 kJ/m2 in Izod impact resistance. It was observed that increasing the weight percentage of fillers in composites causes insufficient interfacial interaction between the matrix and fibers, thereby decreasing their impact resistance. The load transmission between the matrix and fibers is increased by the presence of MWCNTs/SiO2 at the fiber/matrix interface, which also improves the fracture toughness. According to images obtained by Scanning Electron Microscopy of the fracture surfaces of impact-tested specimens, the major reasons for failure include fiber/matrix deboning, fiber breaking, fiber fracture and fiber pull-out.
Investigation of Microstructural Properties of Nano-modified Concrete for Sustainable Environment
Authors: K. Srinivasan  , S. Vivek  , K. Mujiburrahman
Published: March 2024

The creation and evaluation of Nano-modified concrete, with an emphasis on its microstructural characteristics, is the main goal of this extensive study. The inclusion of nanosilica and nanoclay not only enhances the characteristics of concrete but also contributes to mitigating soil pollution. By adding nanosilica and nanoclay as additional cementitious materials, the study intends to assess the structural integrity of nano-modified concrete using cutting-edge techniques like Scanning electron microscopy, Transition electron microscopy and X-ray diffraction. Four different concrete compositions with variable amounts of nanosilica and nanoclay additions (0%, 5%, 10% and 15% of nano additives by weight of fine aggregate) and a 3% cement replacement rate were cast and evaluated throughout the experimental phase. A comparison with regular concrete revealed significant improvements in microstructures, demonstrating the efficacy of nano-modified concrete without sacrificing necessary characteristics. Slump values increased with the addition of nano-silica and nanoclay, indicating better workability and smoother concrete surfaces. The study's findings indicate that the development of Nano-modified concrete has great potential as an advanced building material. In addition to providing instant structural gains, the use of nanosilica and nanoclay enhances the long-term performance of concrete buildings and creates new opportunities for creative and long-lasting building techniques.
Exploring the Effect of Engineered Nanomaterials on Soil Microbial Diversity and Functions: A Review
Authors: Anurag Yadav  , Kusum Yadav
Published: March 2024

This review explores the impact of engineered nanomaterials (ENMs) on soil microbial diversity, function, metabolic pathways, and resilience. With the increasing application of ENMs in agriculture and industrial fields, understanding their interaction with soil microorganisms is crucial. We examine various types of ENMs, their physicochemical properties, and how these influence soil microbial communities. This review highlights the dual role of ENMs, demonstrating both beneficial and detrimental effects on microbial diversity and activity. Fundamental interaction mechanisms, such as altering metabolic pathways and microbial community structure, are discussed. Additionally, we address the implications of ENM-induced changes for soil health and agricultural productivity. Further, the review provides insights into the complex dynamics of ENMs in soil ecosystems and outlines directions for future research to optimize their use while minimizing environmental risks.
Green Synthesis of Barium Sulphate Nanostructures Using Azadirachta indica Leaf Extract
Authors: S. Saravanan  , B. Ananda Kumar  , S. B. Ronald  , Ch. Udaya Bhaskara Rao
Published: March 2024

Green synthesis of nanostructures is a growing technology owing to its potential applications in various fields. The method is feasible, simple and non-toxic; it is a low-cost strategy. It meets the standards of green chemistry, high crystalline nature and morphological structures. In this work, green synthesis of barium sulphate nanostructure was carried out by using Azadirachta indica (neem) leaf extract, barium chloride dehydrates and anhydrous sodium sulphate as source materials, by co-precipitation method. The as-synthesized barium sulphate nanostructures were subjected to different characterization techniques for their structural, functional, morphological and elemental studies by using XRD, FTIR, SEM and EDX. XRD reveals the orthorhombic crystal phase with a sharp diffraction peaks phase. SEM studies revealed the rice grain-like structures with an average diameter of 71.36 nm. Furthermore, a better understanding of this biological phenomenon may provide new insights for enhancing nanomaterial usage in the future.
Evaluation of Dielectric Properties of Peanut Oil Biodiesel Mixed with Nano-additives
Authors: Pakalapati Janaki  , Surakasi Raviteja  , Sista Deepthi  , Pappala Anil Kumar  , Chandaka Durga Prasad  , Bhaskara Rao Amiti
Published: March 2024

The main aim of this study is to assess the electrical characteristics pertaining to a biodiesel derived from peanut oil mixed with magnesium oxide (MgO) and zinc oxide (ZnO) nano-additives. After synthesizing biodiesel from peanut oil by the transesterification process, it is combined with MgO and ZnO nano-additives in varying proportions: 100 ppm MgO, 100 ppm ZnO and 50 ppm MgO + 50 ppm ZnO, of the overall volume. The measurement and analysis of biodiesel blends necessitate consideration of crucial electrical parameters, including breakdown voltage, resistivity, permittivity and electrical conductivity. A positive association was found between the quantity of nano-additives and resistivity. The potential cause for the enhancement of the electrical properties might be attributed to the dispersion of the nano-additives. The peanut oil dispersed with 100 ppm MgO exhibited desirable dielectric properties.
Bioremediation of Kraft Lignin in Wastewater: Optimization of Temperature and Isolation of Valuable Compounds
Authors: C. Swati  , J. Anandkumar
Published: March 2024

Conventional methods for the treatment of complex lignin found in the pulp and paper mill effluent is a strenuous and expensive process. Microbial degradation is a promising technique to degrade lignin efficiently due to its adaptability and rapid growth of microbes in diverse environments. This study is focused on the isolation of potential ligninolytic bacterial strains from agricultural soil and decomposed wood sources for successful degradation of lignin present in the wastewater. Initially, 15 ligninolytic strains were identified and three dominant species, Staphylococcus lentus (SB5), Bacillus megaterium (RWB15) and Pseudomonas geniculata (RWP9) were isolated as per their growth tolerance pattern with different lignin concentrations. The lignin degradation study was carried out at different temperatures (25-45℃) with 1000 mg/l of feed lignin concentrations. The optimum degradation temperature of all the strains fell within the range 30-35℃. The maximum lignin degradation of SB5, RWB15 and RWP9 was identified as 89, 77 and 90% at the end of the 6th, 3rd and 7th day of biodegradation, respectively. There was a steep reduction of COD by all three microbes before attaining the stationary phase and thereafter COD reduction was sluggish due to the death phase. Besides, the microbes used in this study showed the transformation of lignin into valuable low-molecular by-products, vanillin, vanillic acid and adipic acid with their concentration being quantified as 28, 101 and 130 mg/l, respectively. This study shows the successful degradation of waste lignin and the recovery of valuable byproducts from waste streams.
Biosynthesis of Zinc Oxide Nanoparticles using Cleome gynandra Extract and Evaluation of its Cytotoxic Activities on A549 Cell Line
Authors: V. Velmani  , M. Balaji  , P. Rajesh  , G. T. Parethe  , S. Kavica
Published: March 2024

Zinc oxide nanoparticles (ZnONPs) were green synthesised by a simple, rapid, eco-friendly and a cheaper method using Cleome gynandra plant extract. The ZnONPs were characterized using UV- Visible Spectroscopy, FT-IR, XRD, FE-SEM and EDX analysis. The formation of ZnONPs (355 nm) was confirmed by UV visible spectroscopy. The crystalline nature of the nanoparticles was studied by XRD. The presence of different functional groups in the biomolecules was evident from FT-IR spectrum. The morphology of ZnONPs was analysed using SEM and the presence of zinc oxide was confirmed through elemental analysis. They were also analyzed for their biological and antioxidant activities. The green synthesized ZnONPs exhibited a good antibacterial activity against both Gram-negative and Gram-positive bacteria. Furthermore, they exhibited appreciable anticancer activity on the lung (A549) cancer cell lines.
Current Scenario and Future Perspectives of Renewable and Sustainable Energy in India: Progress and its Challenges
Authors: A. S. Sikarwar  , N. A. Ansari  , P. Singh
Published: March 2024

Energy is a key force behind both social and economic advancement. The scientific advancements in numerous industrial, governmental, and municipal activities have significantly increased the energy demand. The main reasons behind the efficient utilization of renewable energy sources (RESs) are the rapidly increasing rates of energy demand and fuel prices, as well as the requirement to control greenhouse gas emissions. In reality, meeting the world’s growing energy requirements and preventing climate change are now of greatest concern. This review paper provides a thorough overview of the creation and growth of renewable and sustainable energy sources, including information on their types, traits, benefits, and drawbacks. This review specifically discusses the situation and future potential of renewable and sustainable energy sources in India. The growth of RESs can have a substantial impact on the economic development of India, in addition to creating employment possibilities related to harnessing energy from RESs.
Effect of Copper Inclusion in Zinc sulfide Thin Films for Photocatalytic Applications
Authors: T. Shobana  , R R. Sakthi Sudar Saravanan , D. Kathirvel
Published: March 2024

Transparent and well-adhered pure zinc sulfide (ZnS) and different concentrations of copper-doped zinc sulfide thin films were obtained on glass substrates by the Chemical bath deposition process. Zinc acetate, copper acetate and thiourea were employed as sources of Zn2+, Cu2+ and S2- ions, respectively; ammonia and hydrazine hydrate served as complexing agents for the preparation of pure zinc sulfide and different concentrations of copper-doped zinc sulfide thin films. By adjusting the ammonia concentration, the prepared solution pH was maintained at 11. The prepared samples were deposited at the rates of 60 and 90 minutes each, with the bath temperature being held at 80 °C. The structural, morphological and optical properties of the prepared films were characterized by XRD, FE-SEM and EDX, and the results were reported. The XRD patterns revealed that all thin films possess a polycrystalline cubic zinc blended structure and that the prepared pure and copper-doped ZnS thin films have good crystallinity; the crystallite sizes were less than 20 nm. From the FE-SEM spectra, it is understood that the pure and Cu-doped ZnS thin films were uniformly coated with spherical morphology. The surface morphology, optical characteristics and deposition mechanism were all obviously impacted by the ammonia concentration. Additionally, under UV light irradiation, the effect of the photocatalytic property of the prepared thin films with methylene blue dye was studied and the corresponding dye degradation graphs were reported.
Influence of Novel Al-Ni Electrodes on Roughness and Machining Time in Inconel 625 EDM Machining: A Comprehensive RSM Performance Analysis
Authors: Y. Justin Raj  , A. Bovas Herbert Bejaxhin  , S. Raj Kumar  , G. M. Balamurugan
Published: March 2024

In the context of Inconel 625 machining, this study explores the effects of novel Al-Ni nano electrodes on surface roughness and machining time. Thorough performance study was undertaken to clarify the complex connections between the machining settings, electrode composition, and final surface quality. Important insights were obtained via methodical experimentation and data analysis, which helps optimize the machining procedures for improved productivity and surface quality when milling Inconel 625. This research presents an experimental investigation of the effects of the Electric Discharge Machining (EDM) input parameters, namely current, pulse-on time, and pulse-off time, on the surface roughness and machining time output parameters. Inconel 625 was the material of choice for the work piece. Electric discharge machining oil was used as the dielectric fluid and aluminium nanocomposite as the tool electrode. Response surface methodology (RSM) approach was employed in the experimentation. ANOVA was used to optimize the parameters and obtain the lowest possible surface roughness (SR) and machining time. The findings show that pulse-off time is the most significant motivating factor for SR. The current is the main determining factor for machining time. The Central Composite Design approach was used for optimization.
Evaluating Policy to Research Fellowship programmes
Authors: Buckley Nicola , Oliver Kathryn
Published: March 2024

Background:

This paper provides insights into ‘Policy to Research’ (P2R) Fellowships and related programmes within the ‘relationship’ model of academic–policy engagement, which provide structured opportunities for policy officials to interact with academic researchers.

Aims and objectives:

Information is provided on P2R Fellowship and similar programmes in the UK, Europe and North America. The research questions concern the aims, features and intended outcomes of P2R Fellowship programmes; what can be learned from evaluations of these programmes; and whether value for money for these programmes can be deduced. The authors then aim to provide guidance for an evaluation framework.

Methods:

Programmes were identified through a subset of data gathered on research–policy engagement initiatives in a recent mapping exercise. This was supplemented via Google search. Published data on organisational websites is presented in a table, where data was checked by email with programme managers, who were also asked to provide additional evaluation documents.

Findings:

Twenty-four P2R Fellowship programmes were located. Eleven programme managers confirmed information provided in Table 1. Evaluation documents were provided for five programmes. An average cost of providing a P2R Fellowship was estimated at around £5,000 for each Fellow. Five common aims for P2R Fellowship programmes were identified.

Discussion and conclusion:

Quantitative and qualitative evaluations available from the 24 programmes are reviewed. The comparative lack of published evaluation data is discussed, and recommendations made for an evaluation framework for P2R Fellowships, to build understanding of how to intervene successfully to support a research-for-policy system which delivers for all.
Non-abelian p -adic Rankin-Selberg L -functions and non-vanishing of central L -values
Authors: Januszewski Fabian
Published: March 2024

abstract: We construct $p$-adic $L$-functions for torsion classes for $\GL(n+1)\times\GL(n)$ and along the way prove new congruences between special values of Rankin-Selberg $L$-functions for $\GL(n+1)\times\GL(n)$ over arbitrary number fields. This allows us to control the behavior of $p$-adic $L$-functions under Tate twists and to prove the existence of non-abelian $p$-adic $L$-functions for Hida families on $\GL(n\!+\!1)\linebreak\times\GL(n)$. As an application, we establish generic non-vanishing results for central $L$-values: We give sufficient local conditions for twisted central Rankin-Selberg $L$-values to be generically non-zero.
Polymer-based three-waveguide polarization beam splitter with reduced crosstalk for optical circuitry
Authors: Alam Md Koushik , Afsary Noor , Nijhum Zarin Tasnim , Rasel Md Omar Faruk
Published: March 2024

Polarization beam splitters are pivotal in manipulating polarized light within photonic
integrated circuits for various optical applications. This study
introduces a single-mode polarization beam splitter comprising three
waveguides realized with polymer materials. The device optimization
process employed the beam propagation method, explicitly using the
RSoft CAD BeamProp solver. Our proposed beam splitter performs
exceptionally well with 99% complete and null light transmission
efficiency. In particular, it demonstrates minimal insertion loss
(0.04 dB for complete transmission and 0.07 dB for null
transmission) and low coupling loss (0.03 dB and 0.04 dB
for complete transmission, 21.9 dB and 36.3 dB for null
transmission from input to bridge and bridge to output waveguides,
respectively). Additionally, the beam splitter showcases significantly
reduced crosstalk: −27dB and −26.98dB for TE modes during complete light
transfer, and −36.28dB and −33.61dB for TM modes during null light
transfer. These results underscore its potential for advancing
integrated optical systems.
Collagen organization and structure in FBLN5-/- mice using label-free microscopy: implications for pelvic organ prolapse
Authors: Jennings Christian M. , Markel Andrew C. , Domingo Mari J. E. , Miller Kristin S. , Bayer Carolyn L. , Parekh Sapun H.
Published: March 2024

Pelvic organ prolapse (POP) is a gynecological disorder described by the descent of superior pelvic organs into or out of the vagina as a consequence of disrupted muscles and tissue. A thorough understanding of the etiology of POP is limited by the availability of clinically relevant samples, restricting longitudinal POP studies on soft-tissue biomechanics and structure to POP-induced models such as fibulin-5 knockout (FBLN5-/-) mice. Despite being a principal constituent in the extracellular matrix, little is known about structural perturbations to collagen networks in the FBLN5-/- mouse cervix. We identify significantly different collagen network populations in normal and prolapsed cervical cross-sections using two label-free, nonlinear microscopy techniques. Collagen in the prolapsed mouse cervix tends to be more isotropic, and displays reduced alignment persistence via 2-D Fourier transform analysis of images acquired using second harmonic generation microscopy. Furthermore, coherent Raman hyperspectral imaging revealed elevated disorder in the secondary structure of collagen in prolapsed tissues. Our results underscore the need for in situ multimodal monitoring of collagen organization to improve POP predictive capabilities.
A joint calibration method for monocular speckle structured light system
Authors: Jiang Zhaoxiang , Liang Rongshen , Tian Jindong
Published: March 2024

We propose a novel and flexible method for calibrating monocular speckle structured light system (MSSLS). The proposed method uses only camera intrinsic parameters, projector center coordinate, and reference plane equation as the calibration parameters, and can be easily implemented using a circle grid calibration board and an unmarked planar target arranged with arbitrary distance and tilt angle. A joint reprojection error function is constructed to obtain globally optimal calibration parameters. A method for correcting the perspective deformation and lens distortion of the reference speckle image is also proposed, facilitating the application of stereo matching algorithms for disparity calculation. Based on consumer-grade MSSLS, the effectiveness and accuracy of the proposed method are verified by experiments.
Advancing large-scale thin-film PPLN nonlinear photonics with segmented tunable micro-heaters
Authors: Li Xiaoting , Li Haochuan , Wang Zhenzheng , Chen Zhaoxi , Ma Fei , Zhang Ke , Sun Wenzhao , Wang Cheng
Published: March 2024

Thin-film periodically poled lithium niobate (TF-PPLN) devices have recently gained prominence for efficient wavelength conversion processes in both classical and quantum applications. However, the patterning and poling of TF-PPLN devices today are mostly performed at chip scales, presenting a significant bottleneck for future large-scale nonlinear photonic systems that require the integration of multiple nonlinear components with consistent performance and low cost. Here, we take a pivotal step towards this goal by developing a wafer-scale TF-PPLN nonlinear photonic platform, leveraging ultraviolet stepper lithography and an automated poling process. To address the inhomogeneous broadening of the quasi-phase matching (QPM) spectrum induced by film thickness variations across the wafer, we propose and demonstrate segmented thermal optic tuning modules that can precisely adjust and align the QPM peak wavelengths in each section. Using the segmented micro-heaters, we show the successful realignment of inhomogeneously broadened multi-peak QPM spectra with up to 57% enhancement of conversion efficiency. We achieve a high normalized conversion efficiency of 3802%  W−1  cm−2 in a 6 mm long PPLN waveguide, recovering 84% of the theoretically predicted efficiency in this device. The advanced fabrication techniques and segmented tuning architectures presented herein pave the way for wafer-scale integration of complex functional nonlinear photonic circuits with applications in quantum information processing, precision sensing and metrology, and low-noise-figure optical signal amplification.
Two-dimensional flow vector measurement based on all-fiber laser feedback frequency-shifted multiplexing technology
Authors: Zhang Lei , Lv Jialiang , Zhao Yunkun , Li Jie , Liu Keyan , Yu Qi , Li Hongtao , Yu Benli , Lu Liang
Published: March 2024

The decomposition and identification of signals are crucial for flow vector acquisition in a multi-dimensional measurement. Here, we proposed a two-dimensional (2D) flow vector measurement system based on all-fiber laser feedback frequency-shifted multiplexing technology. The reliable performance of the system is characterized by experimental verification and numerical simulation. An orthogonal dual-beam structure is employed to eliminate the impact of an unknown incident angle in the practical application. Meanwhile, the vector velocity signals in 2D can be decomposed into one-dimensional (1D) scalar signals by adopting the frequency-shifted multiplexing, which makes it easy to obtain the vector information and velocity distribution of fluid motion through the self-mixing interference frequency spectrum. Moreover, the measured flow rates present a high linearity with syringe pump speeds ranging from 200 to 2000 μL/min, and the velocity information of the different incidence angles is easily obtained with high precision. This work may pave the way for the acquisition and processing of multi-dimensional flow vector signals, with potential applications in biomedical monitoring and microflow velocity sensing.
Modeling resistance to the broadly neutralizing antibody PGT121 in people living with HIV-1
Authors: Cassidy Tyler , Stephenson Kathryn E. , Barouch Dan H. , Perelson Alan S.
Published: March 2024

PGT121 is a broadly neutralizing antibody in clinical development for the treatment and prevention of HIV-1 infection via passive administration. PGT121 targets the HIV-1 V3-glycan and demonstrated potent antiviral activity in a phase I clinical trial. Resistance to PGT121 monotherapy rapidly occurred in the majority of participants in this trial with the sampled rebound viruses being entirely resistant to PGT121 mediated neutralization. However, two individuals experienced long-term ART-free viral suppression following antibody infusion and retained sensitivity to PGT121 upon viral rebound. Here, we develop mathematical models of the HIV-1 dynamics during this phase I clinical trial. We utilize these models to understand the dynamics leading to PGT121 resistance and to identify the mechanisms driving the observed long-term viral control. Our modeling highlights the importance of the relative fitness difference between PGT121 sensitive and resistant subpopulations prior to treatment. Specifically, by fitting our models to data, we identify the treatment-induced competitive advantage of previously existing or newly generated resistant population as a primary driver of resistance. Finally, our modeling emphasizes the high neutralization ability of PGT121 in both participants who exhibited long-term viral control.
Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models
Authors: Shao Yucai , Magee Andrew F. , Vasylyeva Tetyana I. , Suchard Marc A.
Published: March 2024

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.
The impact of icodextrin on the outcomes of incident peritoneal dialysis patients
Authors: Wang I-Kuan , Chan Chan Ip , Lin Alfred Hsing-Fen , Yu Tung-Min , Yen Tzung-Hai , Lai Ping-Chin , Li Chi-Yuan , Sung Fung-Chang
Published: March 2024

Objective

The aim of the study is to investigate the effects of icodextrin on the risks of death, technique failure and the first episode of peritonitis in peritoneal dialysis (PD) patients.

Methods

From medical records of a medical center in Taiwan, a total of 725 newly diagnosed end-stage kidney disease patients receiving PD for at least 90 days from January 1, 2007 to December 31, 2018 were identified. These patients were grouped as 190 icodextrin users and 535 non-users. Users were defined as utilization of icodextrin for ≥ 50% of their PD duration. The use of icodextrin was considered a time-varying exposure in the Cox proportional hazard model. The risks of death, technique failure and the first episode of peritonitis were compared between two cohorts by the end of 2018.

Results

Compared to the non-users, the icodextrin users had significant lower risks of mortality (6.5 vs.7.2 per 100 person-years; adjusted HR = 0.62, 95% CI = 0.42–0.91) and technique failure (12.7 vs. 15.2 per 100 person-years; adjusted HR = 0.61, 95% CI = 0.47–0.81), and the first peritonitis episode (5.0 vs. 17.0 per 100 person-years; adjusted HR = 0.22, 95% CI = 0.14–0.35). The risk of peritonitis reduced further in icodextrin users with diabetes and with cardiovascular disease.

Conclusion

Icodextrin was associated with lower risks of mortality, technique failure, and the first episode of peritonitis.
Retrospective analysis of percutaneous intervention of the renal artery in transplanted kidneys in children and adolescents at a tertiary public hospital
Authors: Faccinetto Ana Carolina Buso , Santos Gustavo Rocha Feitosa , Taguchi Juliana Cristina , Orellana Henry Campos , Galhardo Attílio , Kanhouche Gabriel , Barteczko Manoela Linhares Machado , Tedesco Júnior Hélio , Bravo-Valenzuela Nathalie Jeanne Magioli , Moises Valdir Ambrósio , Pestana José Osmar Medina , Silva Célia Maria Camelo , Barbosa Adriano Henrique Pereira
Published: March 2024

Background

This study evaluated the long-term effects of percutaneous intervention in children and adolescents with transplant renal artery stenosis (TRAS).

Methods

Twenty patients had significant stenosis (>50%) and underwent percutaneous transluminal angioplasty (PTA/stenting) (TRAS group-intervention); 14 TNS (non-significant group -control) patients did not have significant stenosis (≤50%) and were treated clinically. The combined primary endpoints were death from all causes and late graft failure. The secondary endpoints were serum creatinine (SCr), systolic blood pressure (SBP), and diastolic blood pressure (DBP).

Results

No statistically significant difference was found between TRAS—Intervention(N = 20) and TNS groups—Control (N = 14) for these clinical parameters: deaths, 1 (5.0%) vs. 0 (0.0%) (p = 1.000) and graft loss, 4 (20.0%) vs. 2 (14.3%) (p = 1.000). For the secondary endpoints, after 1 month and 1 year the values of SCr, SBP, and DBP were similar between the two groups but not statistically significant.

Discussion

In the TRAS group (intervention), the stent implantation was beneficial for treating refractory hypertension and reducing blood pressure (BP) in children and adolescents. Despite the outcomes being similar in the two groups, it can be inferred that the patients in the TRAS group (intervention) would have had a worse outcome without the percutaneous intervention.

Conclusion

TRAS treatment with stenting can be considered for children and adolescents. Because the sample in the present study comprised of only a specific population, further studies are needed for generalization.

Trial registration

The trial was registered at clinictrials.gov with trial registration number NCT04225338.
Culture, prefrontal volume, and memory
Authors: Barber Nicolette , Valoumas Ioannis , Leger Krystal R. , Chang Yu-Ling , Huang Chih-Mao , Goh Joshua Oon Soo , Gutchess Angela
Published: March 2024

Prior cross-cultural studies have demonstrated differences among Eastern and Western cultures in memory and cognition along with variation in neuroanatomy and functional engagement. We further probed cultural neuroanatomical variability in terms of its relationship with memory performance. Specifically, we investigated how memory performance related to gray matter volume in several prefrontal lobe structures, including across cultures. For 58 American and 57 Taiwanese young adults, memory performance was measured with the California Verbal Learning Test (CVLT) using performance on learning trial 1, on which Americans had higher scores than the Taiwanese, and the long delayed free recall task, on which groups performed similarly. MRI data were reconstructed using FreeSurfer. Across both cultures, we observed that larger volumes of the bilateral rostral anterior cingulate were associated with lower scores on both CVLT tasks. In terms of effects of culture, the relationship between learning trial 1 scores and gray matter volumes in the right superior frontal gyrus had a trend for a positive relationship in Taiwanese but not in Americans. In addition to the a priori analysis of select frontal volumes, an exploratory whole-brain analysis compared volumes—without considering CVLT performance—across the two cultural groups in order to assess convergence with prior research. Several cultural differences were found, such that Americans had larger volumes in the bilateral superior frontal and lateral occipital cortex, whereas Taiwanese had larger volumes in the bilateral rostral middle frontal and inferior temporal cortex, and the right precuneus.