bluuebunny/crossref_metadata_2025_split huggingface dataset:
In situ tuning of optomechanical crystals with nano-oxidation
Authors: Hatipoglu Utku , Sonar Sameer , Lake David P. , Meesala Srujan , Painter Oskar 
Published: February 2024

Optomechanical crystals are a promising device platform for quantum
transduction and sensing. Precise targeting of the optical and
acoustic resonance frequencies of these devices is crucial for future
advances on these fronts. However, fabrication disorder in these
wavelength-scale nanoscale devices typically leads to inhomogeneous
resonance frequencies. Here we achieve in
situ, selective frequency tuning of optical and acoustic
resonances in silicon optomechanical crystals via electric
field-induced nano-oxidation using an atomic-force microscope. Our
method can achieve a tuning range >2nm (0.13%) for the optical resonance
wavelength in the telecom C-band, and >60MHz (1.2%) for the acoustic resonance
frequency at 5 GHz. The tuning resolution of 1.1 pm for
the optical wavelength and 150 kHz for the acoustic frequency
allows us to spectrally align multiple optomechanical crystal
resonators using a pattern generation algorithm. Our results establish
a method for precise post-fabrication tuning of optomechanical
crystals. This technique can enable coupled optomechanical resonator
arrays, scalable resonant optomechanical circuits, and frequency
matching of microwave-optical quantum transducers.
Evaluation and screening of technology start-ups based on PCA and GA-BPNN
Authors: Li Jiaxin , Meng Mingming , Liu Xin , Lv Yanjie , Yu Jian 
Published: February 2024

Purpose
Due to the existence of information opacity, there is a common problem of adverse selection in the process of screening alternative technology start-ups (TSs) and determining investment targets by venture capital institutions, which does not reveal the true value of enterprises and makes the market inefficient. The aim of this paper is to design an evaluation and screening system help venture capital institutions to select the qualified TSs as their investment objective.

Design
A research framework of four dimensions that include conception, technical innovation, business model and team structure, was built based on previous studies. Based on the research framework, 15 second-level indicators and 33 third-level indicators were extracted with literature research method. This paper proposes an evaluation model with back propagation neural network (BPNN) optimized by genetic algorithm (GA) to improve the rate of selecting and investing in qualified start-ups.

Findings
The results show that the evaluation accuracy of the evaluation model for qualified and unqualified enterprises can reach 80.33% and 93.67% respectively, which has verified the effectiveness of the model and algorithm.

Originality/Value
This paper established an effective evaluation system based on PCA and GA-BPNN to help venture capital institutions preliminarily screen potential technology start-ups, which provides the possibility for venture capital institutions to greatly reduce the screening time and cost, improve the screening efficiency of TSs, and scientifically assess the risk of investee projects or investee enterprises to obtain sustainable and stable excess profits.
Comparison of predicting cardiovascular disease hospitalization using individual, ZIP code-derived, and machine learning model-predicted educational attainment in New York City
Authors: Takkavatakarn Kullaya , Dai Yang , Hsun Wen Huei , Kauffman Justin , Charney Alexander , Coca Steven G. , Nadkarni Girish N. , Chan Lili 
Published: February 2024

Background
Area-level social determinants of health (SDOH) based on patients’ ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could be used to derive individual SDOH measures, specifically individual educational attainment, is unknown.

Methods
This is a retrospective study using data from the Mount Sinai BioMe Biobank. We included participants that completed a validated questionnaire on educational attainment and had home addresses in New York City. ZIP code-level education was derived from the American Community Survey matched for the participant’s gender and race/ethnicity. We tested several algorithms to predict individual educational attainment from routinely collected clinical and demographic data. To evaluate how using different measures of educational attainment will impact model performance, we developed three distinct models for predicting cardiovascular (CVD) hospitalization. Educational attainment was imputed into models as either survey-derived, ZIP code-derived, or ML-predicted educational attainment.

Results
A total of 20,805 participants met inclusion criteria. Concordance between survey and ZIP code-derived education was 47%, while the concordance between survey and ML model-predicted education was 67%. A total of 13,715 patients from the cohort were included into our CVD hospitalization prediction models, of which 1,538 (11.2%) had a history of CVD hospitalization. The AUROC of the model predicting CVD hospitalization using survey-derived education was significantly higher than the model using ZIP code-level education (0.77 versus 0.72; p < 0.001) and the model using ML model-predicted education (0.77 versus 0.75; p < 0.001). The AUROC for the model using ML model-predicted education was also significantly higher than that using ZIP code-level education (p = 0.003).

Conclusion
The concordance of survey and ZIP code-level educational attainment in NYC was low. As expected, the model utilizing survey-derived education achieved the highest performance. The model incorporating our ML model-predicted education outperformed the model relying on ZIP code-derived education. Implementing ML techniques can improve the accuracy of SDOH data and consequently increase the predictive performance of outcome models.
Zentralbibliothek im KAP1 – vom Logistikgebäude zur „Bibliothek des Jahres 2023“
Authors: Kahmann Karoline , Kamp Norbert , Leschner Martina , Schwering Stephan 
Published: February 2024

Zusammenfassung
Dieser Artikel beschreibt die Vision, das Konzept und den Erfolg der neuen Zentralbibliothek im KAP1 in Düsseldorf: Neueröffnung 2021 und 2023 Bibliothek des Jahres. Die neue Zentralbibliothek in dem umgebauten Logistikgebäude bringt die Menschen in der Stadt zusammen und legt den Fokus nicht auf die Medienausleihe, sondern vor allem auf die Aufenthaltsqualität und hohe Zugänglichkeit (Sonntagsöffnung). 14 Veranstaltungsbereiche, 600 Arbeitsplätze, ein Café, Kinderbibliothek, Jugendbibliothek, Musikbibliothek mit -studio und LibraryLab machen aus einem ehemaligen Postgebäude einen lebendigen Kulturhotspot mitten in der Stadt.
n-Defendant Litigation and Settlement: The Impact of Joint and Several Liability
Authors: Kornhauser Lewis A. , Takeda Keith T. 
Published: February 2024

Abstract
This article generalizes the analysis of settlement under joint and several liability from lawsuits involving one plaintiff and two defendants to those involving n ≥ 2 defendants. We demonstrate that, depending upon the correlation of outcomes among the defendants, but regardless of the distribution of liability shares, joint and several liability may encourage plaintiffs to select some defendants for litigation while settling with those remaining. In particular, under joint and several liability, when each defendant is grouped with others sharing correlated outcomes, and the plaintiff’s probability of success against any defendant is sufficiently high, we show that, in all Nash equilibrium, the plaintiff litigates against the defendant from each group with the smallest share and settles with all other defendants. There are a continuum of equilibria but they are all payoff-equivalent up to permutation. Plaintiff’s payoff is identical in all equilibria; only the payoffs of the members with the smallest share within a group are permuted. We also show that, for sufficiently high plaintiff’s probability of success, this result holds even when the defendants are allowed to form coalitions, and derive the set of offers in the behaviorally unique coalition proof Nash equilibrium; as before, these offers induce litigation against the defendant with the smallest share in each group and settlement with all other defendants.
Potential Elitism in Selection to Bilingual Studies: A Case Study in Higher Education
Authors: Barrado-Timón Diego A. 
Published: February 2024

Abstract
This research provides information toward answering the question of whether bilingual studies at the university level might be elitist. This is a recurring research topic in terms of using English for nonlanguage instruction at the primary and secondary levels, but very few studies refer to university education. We seek to fill that gap in the literature by way of a case study centered on the International Studies degree offered by the Universidad Autónoma de Madrid in Spain. A survey was conducted of students in this program inquiring as to the educational and language levels of their parents as well as their possibilities for exposure to English during secondary (high school) education. The analysis of this quantitative data, student’s grades, and qualitative responses gathered through interviews with program professors does not allow us to affirm the presence of class bias in said institution during student selection for the bilingual track; nor are students in the bilingual group found to have obtained better academic outcomes than their peers in the monolingual group.
Effect of asphalt modified with waste engine oil on the durability properties of hot asphalt mixtures with reclaimed asphalt pavement
Authors: Abd Ali Nadia S. , Joni Hasan H. , Al-Rubaee Rasha H. A. 
Published: February 2024

Abstract
The increased demand for asphalt and other materials involved in the construction of pavement led to an increase in the cost of these materials, which calls for searching for alternatives to virgin materials that can be used to produce asphalt mixtures. Reclaimed asphalt pavement (RAP) was employed in this study and regenerated using oxidized asphalt modified with waste engine oil (WEO). This method can achieve economic and environmental benefits. After improving the properties of oxidized asphalt using WEO, it was used with reclaimed asphalt mixtures (RAP). When the RAP was added at ratios of 20, 30, 40, and 50%, an improvement can be noticed in the mechanical performance of the asphalt mixtures renewed with oxidized asphalt and WEO and an increase in its resistance to stripping. When reclaimed asphalt pavement (RAP) is added to hot mix asphalt (HMA) at concentrations of 20, 30, 40, and 50%, respectively, the Marshall stability of HMA is improved by 10, 20, 28, and 9.5%, the flow is declined by 1% for all ratios of RAP except for 50% RAP where the flow decline by 3%, the unit weight is enhanced, the quantity of air voids in the mix is preserved within allowable ranges, and the resistance to stripping is increased by 62, 77, 85, and 76%, respectively. Research also shows that incorporating 40% RAP enhances the resistance to moisture by about 5.9%. The addition of 40% RAP reduced the Cantabro loss values by about 2 and 16% for both aging and non-aging samples, respectively. The rutting resistance increased by 50 and 47% for mixes with 40% RAP at 50 and 60°C, respectively. As a result, it became evident that mixtures containing RAP material could be effectively adapted to satisfy the relevant volumetric and performance requirements.
Phytochemical characterisation and toxicity effect of Tithonia diversifolia (Hemls.) A. Gray leaf extract on fall army worm Spodoptera frugiperda (JE Smith) larvae
Authors: Oluwamodupe Cecilia , SB Suby , Olayeriju Olanrewaju Sam , Suresh Kumar 
Published: February 2024

Abstract

Objectives
To mitigate the losses due to fall armyworm (FAW) infestation in maize, chemical pesticides had been the first choice and widely used as an emergency response. However, it comes with attendant health effect. This necessitates the development of plant based effective and safer pesticides. This research investigate response of fall armyworm larvae when they are exposed to crude and partially purified Tithonia diversifolia leaf extract.

Methods
Chemical constituent of the extract was identified using NIST08.LIB library spectra provided by the software on a GC-MS system and FTIR analysis was done using KBr pellet technique with a resolution and scanning speed of 4 cm−1 and 2 mm/s. Dose dependent toxicity assay of T. diversifolia extracts on FAW at different growth stages under controlled environment in laboratory, followed by its effect under phytotron were examined against control and azadirachtin from neem.

Results
The GC-MS of the butanol eluent revealed 20 compounds out of which the major ones being beta-d-glucopyranoside, methyl (15.225 %) palmitic acid, TMS derivative (10.98 %) and hexadecanoic acid, 2-[(trimethylsily)oxy]-, methyl ester (8.75 %). The FT-IR spectroscopic analysis of the butanol eluent of T. diversifolia leaf extract revealed the presence of alcohols, phenols, aldehydes, ketones, alkanes and primary amines. The butanol eluent and crude extract caused 96 % mortality at neonate and first instar FAW larvae.

Conclusions
The toxic and repellant effects revealed by diet bioassay and phytotron experiment respectively suggest that butanol eluent of T. diversifolia leaf extract could be a good and effective target for biopesticide production against FAW.
Cylindrical vector beam multiplexing holography employing spin-decoupled phase modulation metasurface
Authors: Xie Zhiqiang , Liang Zeming , Wu Haisheng , Zeng Qingji , Guan Zhiwei , Long Aofan , Zhong Pin , Liu Junmin , Ye Huapeng , Fan Dianyuan , Chen Shuqing 
Published: February 2024

Abstract
Cylindrical vector beams (CVBs) hold considerable promise as high-capacity information carriers for multiplexing holography due to their mode orthogonality. In CVB holography, phase holograms are encoded onto the wave-front of CVBs with different mode orders while preserving their independence during reconstruction. However, a major challenge lies in the limited ability to manipulate the spatial phase and polarization distribution of CVBs independently. To address this challenge, we propose a spin-decoupled phase modulation strategy by leveraging the propagation and geometric phase of composite phase metasurfaces. By exploiting the polarized Poincaré sphere, we show that CVBs can be decomposed into two circularly polarized components with orthogonal polarization states and conjugate phase distributions. This decomposition enables independent control of the phase and polarization distributions of CVBs by modulating the initial phase and phase difference of these two components. Consequently, two holograms with discrete spatial frequency distributions that carry opposite helical phases are encoded to modulate the wave-front of CVBs by the metasurface consisting of Si nanopillars. This allows for us to achieve successful four-channel CVB multiplexing holography. Benefiting from the non-dispersive nature of geometric phase, this metasurface exhibits a broad operating band spanning the entire visible light spectrum (443 nm–633 nm). These suggest that our proposed method offers comprehensive control over the spatial phase and polarization of CVBs, thereby holding significant potential for advancing their application in holography.
Microfabricated potentiometric sensor based on a carbon nanotube transducer layer for selective Bosentan determination
Authors: Trabik Yossra Ahmed , Ismail Reham Abd El-Aziz , Ayad Miriam Farid , Hussein Lobna Abd El-Aziz , Mahmoud Amr Mohamed 
Published: February 2024

Abstract
In this work, a solid-state electrochemical sensor relying on potentiometric transduction was constructed and optimized to detect Bosentan (BOS) in its pharmaceutical dosage form and human plasma. BOS is useful in pulmonary hypertension management as a nonselective endothelin receptor antagonist. A printed circuit board has been constructed and used as a substrate for microfabricated Cu electrodes. In comparison to a microfabricated control (Cu/ISM) electrode, the sensor potential signal drift was enhanced, and the response time was reduced by using multi-walled carbon nanotubes (MWCNTs) as an ion-to-electron transducer layer. According to IUPAC requirements, the suggested BOS sensors have been electrochemically characterized, and the linear dynamic range is (1.0 × 10−8 to 1.0 × 10−5) M with a limit of detection of 6.28 × 10−9 M and 6.12 × 10−9 M for MWCNT-based sensor (Cu/CNT-NC/ISM) and control sensor (Cu/ISM), respectively. The described sensors have been used successfully to selectively determine BOS in dosage form and human plasma without any pre-treatment steps.
Digital Health Technologies in Vision Care: Transforming Diagnostics and Management
Authors: Gaurav Pfranjpe Et al. 
Published: February 2024

A significant change in the diagnosis and treatment of ocular disorders has resulted from the integration of digital health technology in the field of ophthalmology. This thorough analysis looks at the broad influence and uses of digital solutions in vision care, including wearable technology, teleophthalmology, diagnostic tools, and artificial intelligence (AI) algorithms.
With the use of digital imaging methods like fundus photography and optical coherence tomography (OCT), physicians may now see ocular components with previously unheard-of accuracy. These imaging modalities provide early illness identification and customised treatment plans when combined with AI-driven diagnostic tools.
Platforms for teleophthalmology provide remote screenings, consultations, and monitoring, greatly enhancing access to specialised eye care. Artificial intelligence (AI)-powered telemonitoring systems and mobile applications provide real-time data transfer for effective illness management and prompt treatments.
Perioperative Care Innovations: Optimizing Recovery and Reducing Complications in General Surgery
Authors: C.Z. Pardeshi Et al. 
Published: February 2024

Significant progress has been made in perioperative care for general surgery with the goal of minimising postoperative complications and improving patient outcomes. This thorough analysis examines developments in the preoperative, intraoperative, and postoperative domains of the perioperative continuum. This article explores the most recent innovations influencing the profession, with a focus on patient-centered tactics, technology improvements, and interdisciplinary approaches.
Within the context of preoperative optimisation, therapies aimed at correcting dietary deficiencies, individualised exercise programmes, and psychological preparedness are critical to improving surgical patient readiness. Improved surgical methods, such as robotics and minimally invasive surgery, revolutionise surgical accuracy while reducing trauma and facilitating a quicker recovery.
Innovations in postoperative care, such improved recovery procedures and remote monitoring devices, speed up recovery and lower complications. Pain treatment and infection control advances in pharmacology have a major positive impact on patient comfort and lower morbidity.
This study emphasises the value of customised treatment plans, collaborative decision-making, and specialised communication while embracing patient-centered methods. It highlights how important it is for patients to be involved in their treatment, how to promote their own autonomy, and how to improve compliance with postoperative instructions.
This study seeks to highlight the combined influence of these breakthroughs on changing general surgery perioperative care paradigms through an examination of these advances. The perioperative setting is driven by the combination of innovative tactics, cooperation across varied healthcare specialties, and technology breakthroughs with the ultimate goal of optimising recovery and minimising problems.
Tomato Plant Leaf Disease Detection Using Convolutional Neural Network
Authors: Tejswini S. Danwadkar Et al. 
Published: February 2024

Our country is growing country, India is mostly depended on the agriculture field, and Agriculture is pillar of our country’s economy. Because of this India has to improve in agriculture filed, in many of situations’ farmer face difficulties to detect crop disease in a case large area farm, or late in detection of crop disease in such cases farmer lose their all crop and face the huge loss, to avoid this, in agricultural field is detection of plant diseases is very important. And it is very difficult tasks. In regular normal procedure it requires a more time period and trained person to detect accurate plant disease. In this paper, we proposed effective way for plant disease detection using computer science and machine learning model. Disease transmission from unhealthy plant to all other healthy plants in farm is one of the major damages to crop farm. And these diseases spread like forest fire and have the possible to impact the whole operation if not identified in early on. Now Plant disease detection methods helps to identify infected plants in a very early stage and also help us to identify plant disease in a wide range of area of crops in a cost-effective manner. The aim of this project model is to implement machine learning models, in our proposed system we take a plant leaf image on that leaf images we predict the plant disease using Convolution Neural Networks (CNN) model, in that we build a such a model to predict the plant disease with maximum accuracy and it is for plant disease detection for tomato plant. This machine learning model is analyzing different image metrics pixels data to determine the best performance of network. For that dataset were used around 7around 8016 images we going to use to train the model. We going to use 14 layers CNN models to get better accuracy results. Model consist various layers like convolution, pooling, flatten and dense. Early two layers that is preprocessing and augmentation of images Finally, we get the result of which disease that plant have.
Genetic control of changes in locomotor activity caused by social experience in Drosophilamales
Authors: Bragina Julia V. , Goncharova Anna A. , Besedina Natalia G. , Danilenkova Larisa V. , Kamysheva Elena A. , Kamyshev Nikolai G. 
Published: February 2024

Abstract

Social experience (housing in an unisexual group) modifies locomotor activity in Drosophila. In females, suppression of locomotion occurs only when flies are in aggregations [1], but males retain a lowered level of locomotor activity up to 5 days after their separation from a group [2]. The mechanism by which social experience (housing in a group) affects locomotor activity in Drosophila males is yet unknown. To study the genetic control and clarify the mechanisms of behavioral changes resulting from social experience, we have tested the locomotor activity modifications in various mutants, including those with impaired learning and memory, circadian rhythms, some biochemical pathways, and sensory systems. The results of the present study show that these changes do not seem to be based on the learning and memory mechanisms. The biogenic amines (dopamine and octopamine) seems to play a principal role in the changes in locomotor activity caused by social experience. Also, the dependence of this behavioral modification on olfactory perception was shown. This implies the possible participation of pheromones, which should be verified in future research.
Also, with the same aim, we have performed the screening of our collection of mutants carrying random autosomal insertions of PdLtransposon. Five candidate genes presumably playing a role in behavioral modifications resulting from social experience were revealed (Dek, Hel89B, RpL41, CG11791 and NaCP60E). The results imply a possible role for epigenetic regulation of gene expression in the modification of locomotor behavior caused by social experience.