bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of Stirring in Seawater Freeze Desalination Inside a Cooled Jacketed Crystallizer
Authors: Zhang Hongtao , Savvopoulos Symeon , Islam Md Didarul , Janajreh Isam 
Published: September 2024

Abstract
This study investigates waste brine freeze desalination within a designed, cooled, jacketed crystallizer system. The study combines experimental findings with numerical simulation to interpret the feasibility of this approach. In the experimental phase, actual waste brine samples were collected from several seawater reverse osmosis (RO) units across the Arabian Gulf and analyzed for their ion composition. Furthermore, synthetic concentrated NaCl solution freezing inside the jacketed crystallizer by radial freezing from outer to center with stirring is carried out. The experimental results confirm that stirring enhances desalination efficiency, and it is found that 30 rpm’s efficiency outperforms 60 rpm. Moreover, a computational fluid dynamics (CFD) model of the crystallizer was also developed to understand heat and mass transfer during the freezing process under various conditions. The developed model captures the salinity growth trend, although discrepancies likely result from imperfect insulation at the top and bottom of the crystallizer. The results highlight the crucial role of stirring in homogenizing concentrated brine, effectively preventing the formation of highly concentrated layers at the freezing front. This research underscores the promise of seawater/waste brine freeze desalination as a sustainable and efficient solution for global freshwater scarcity.
Numerical Analysis Comparing the Thermal Performance of Two Solar Chimneys Combined With Thermal Energy Storage Made of Phase Change Materials Embedded in a Metal Foam
Authors: Buonomo Bernardo , Famoso Tommaso Antonio , Golia Maria Rita , Manca Oronzio , Nardini Sergio , Plomitallo Renato Elpidio 
Published: September 2024

Abstract
The two-dimensional numerical analysis of a solar chimney integrated with a phase change material (PCM) wall on a south face of building is the primary goal of this work. While the chimney has a converging channel with a vertical absorbing wall and an angled glass plate, the absorbing capacity wall employs PCM and metal foam.
To identify the most efficient thermal performance, four configurations of the absorbing capacity wall — which serves as a latent thermal energy storage — are studied. The numerical study uses a transient assessment of a two-dimensional airflow model with the Boussinesq assumption and the k-ε turbulence model, where the chimney channel dimensions are given. The finite volume method in Ansys-Fluent is utilized for simulations.
The study examines the thermal and fluid dynamic performance of the phase change material absorbing wall at varying thicknesses. Simulations based on average days in June and December in Aversa, Italy, use aluminium foam-embedded paraffin wax with melting temperatures of 31°C and 42°C. Results include temperature distributions, air velocity, channel profiles, liquid fractions. Understanding the thermal differences between different PCM with metal foam and optimising the energy conversion system are the two main goals of the evaluation.
Inferring Flow Boiling Interfacial Shear Stress Using Physics Informed Neural Networks From Control Volume Models
Authors: Pirnstill Logan M. , Kharangate Chirag 
Published: September 2024

Abstract
Flow boiling has been identified as a promising method for heat acquisition in thermal management technologies. Common issues preventing flow boiling technology from being widely used are variable heat transfer characteristics as well as large pressure drops along the flow boiling channels. These complications arise from the phase change phenomenon and can be rather difficult to predict and characterize. A common approach to predict these phenomena are semi-empirical models, due to their simplicity and basis in well-established physics. These types of models employ a control volume approach where the conservation of mass, momentum, and energy are applied to solve for average quantities like mean vapor and liquid velocities. They are promising as they directly embed physics into solutions while also utilizing correlation-based methods to directly compute complex flow quantities like shear stress. As a result of utilizing correlations to fill in for hard to measure quantities, semi-empirical models act as a prelude to data driven methods in physical modelling. Physics informed neural networks (PINNs) are a recent advancement in the data-driven science and engineering field that also accurately model physics problems using data-driven techniques. In this paper we replace the semi-empirically derived interfacial shear stress term in the momentum equations, which often poorly predicts the interfacial shear stress, with an interfacial shear term informed by a PINN. In general, we find that the PINN is better at fitting the interfacial shear stress term than well-known correlations, with the added benefit of directly being able to include data into the modelling process. This paper demonstrates the effectiveness of data-driven solutions to differential equations for inferring complex flow quantities in under-determined systems, such as these semi-empirical models. Furthermore, applications of PINNs to flow boiling systems will aid in the advancement of thermal management technologies by improving model reliability and incorporation of experimental data directly into the computation process.
Heat Transfer Characteristics of Oscillating Electrohydrodynamic Liquid Flow
Authors: Castaneda Alexander J. , Yagoobi Jamal 
Published: September 2024

Abstract
The current trend in electronic systems sees them continue to develop at a remarkable pace and, thus, they become smaller, more complex, and require larger power densities to operate. Similarly, associated thermal management technologies that support them must continue to advance. The existing world of thermal management systems is typically comprised of heat pipes and loops to dissipate heat from electronics. These systems, despite their ability to transfer heat, are met with the challenge of overcoming mechanical deterioration and are often limited to being passive thermal management methods. Electrohydrodynamic (EHD) conduction pumping is an innovative, low power, and non-mechanical method to pump fluids for thermal management. In addition to these advantages, EHD is also simple in design and is controllable, as it can be integrated into complex and programmable scenarios for optimal thermal management. EHD conduction pumping in unidirectional flows has been successfully explored as a method of enhancing heat transfer and managing fluid flows in both space and terrestrial applications. By designing EHD conduction pumping to oscillate flows, a system is expected to experience further enhanced heat transfer than typical unidirectional pumping due to mixing. This study numerically investigates the concept of using EHD conduction pumping to oscillate a liquid flow to observe the effects on fluid flow behavior, using Novec 7100 as the working fluid. Based on the results, which include enhanced vorticity, and pulsating flow, it is expected that this technology can be used to enhance heat transport. The results of this simulation further support those found in previous experimental studies, and they continue to support the future of EHD conduction pumping as a technology to augment next generation cooling technologies.
Creating Fluid Flow Through Bubble Squeezing in Tapered Microgap
Authors: Shukla Maharshi Y. , Pal Divyprakash , Perez-Raya Isaac , Kandlikar Satish G. 
Published: September 2024

Abstract
A taper microgap is a wedge-shaped cavity placed over a heater surface for enhancing pool and flow boiling heat transfer. Extensive experimental, numerical, and theoretical investigations show that the tapered microgap augments vapor bubbles and liquid movement to enhance critical heat flux and heat transfer coefficient. The current work studies the effect of bubble squeezing with simulated air flow where a bubble grows near the diverging end of a 5° tapered microgap. The bubbles are air-injected at flowrates of 3, 15, and 30 ml/min, and their movement is studied numerically and validated experimentally using a newly developed Arduino Mega 2560-based electromechanical test bench. Qualitative experimental testing validates the numerical method and finds air-injected bubbles leaving from the diverging end of the tapered microgap while drawing working fluid in its wake. In an actual heat transfer system equipped with a tapered microgap, the drawn working fluid will create a flow-like macroconvective current over the heater surface that enhances heat transfer. Results from the current study can be used to expedite tapered microgap development.
Impact of Clean Energy on the Carbon Emission Structure of the Power Grid in China
Authors: Li Xingsheng , Li Wei , Dong Yahong , Sherif S. A. 
Published: September 2024

Abstract
Achieving carbon neutrality is being accelerated by the gradual replacement of traditional high-emission power generation systems with wind and solar energy systems. This development will curb the emission of greenhouse gases (GHGs). This step is especially important in the power transmission and distribution (T&D) network. The purpose of this study is to investigate GHG emissions in the T&D network based on life cycle assessment (LCA). A life cycle carbon assessment (LCCA) model of the T&D network is developed and presented. The inventory of a typical T&D system is presented and the GHG emissions intensity of that system is calculated. It is found that the intensity of GHG emissions of a typical T&D system in China is around 66 gCO2 eq/kWh in 2012. This amount has decreased to around 32 gCO2 eq/kWh in 2022, with the emissions structure remaining mostly unchanged. Electricity loss due to the transmission in a typical T&D network has been found to be responsible for the majority of GHG emissions. A prediction of the timing of carbon neutrality indicates that T&D GHG emissions will account for at least 16% of the total GHG emissions in the power grid in China by the year 2060. This is because solar and wind energy will account for most of the electricity generated.
Thermal Tensegrity
Authors: Conneely Grace E. , Kinzel Gary L. , Juliano Thomas J. , Kinzel Edward C. 
Published: September 2024

Abstract
Several practical problems require high thermal resistance and minimum compliance. An example is a high-temperature computer-controlled stage for additive manufacturing, which must be heated and precisely positioned. In this case, the heat transfer from the build plate must be limited to minimize the heating of the computer-controlled stage. The simplest option, supporting the build plate using low thermal conductivity risers, introduces a tradeoff between the heat transfer to the stage and the mechanical stiffness of the system. We explore an alternative using the concept of tensegrity, a term coined by Buckminster Fuller for structures that are separated only by members in tension. Other objects can be loaded under compression or bending. Because the tensile members can be very slender (for example stainless steel cabling) the overall thermal resistance can be reduced while increasing the mechanical stiffness. We present a solution to a specific problem including practical fabrication considerations and design for manufacturability. We then generalize the design of tensegrity structures to high-temperature thermal applications. Besides the additive manufacturing system, the concept of thermal tensegrity has applications to furnace or kiln design and even connecting high-temperature aircraft skins to structural elements.
Water Depth and Surface Area Extension Correlation Effect on Single Basin Solar Still
Authors: Phillips Agboola 
Published: September 2024

Abstract
This work examines the effect of 4kg, 6kg, 8kg, and 10kg water depth on the efficiency of a passive (single basin solar still) coupled with surface area extension (Fins). Three different configurations of the system were designed and fabricated as follows: SBSS, SBSS4, and SBSS8.
These configurations were studied concurrently while data on the water vapors temperature, absorber plate temperature, covered glass temperature, Ambient temperature, solar irradiation, and daily water production were collected. The empirical findings show that in terms of daily productivity, the SBSS8 performed best with 3.7 kg/m2/day with a water depth of 6kg while SBSS produced the least with 2.3 kg/m2/day with a water depth of 8kg.
A novel GFP-based strategy to quantitate cellular spatial associations in HSV-1 viral pathogenesis
Authors: Arya Deepak , Jaggi Ujjaldeep , Wang Shaohui , Tormanen Kati , Che Mingtian , Mahov Simeon , Jin Ling , Ghiasi Homayon 
Published: September 2024

ABSTRACT

Periodic reactivation of herpes simplex virus type 1 (HSV-1) triggers immune responses that result in corneal scarring (CS), known as herpes stromal keratitis (HSK). Despite considerable research, fully understanding HSK and eliminating it remains challenging due to a lack of comprehensive analysis of HSV-1-infected immune cells in both corneas and trigeminal ganglia (TG). We engineered a recombinant HSV-1 expressing green fluorescent protein (GFP) in the virulent McKrae virus strain that does not require corneal scarification for efficient virus replication (GFP-McKrae). Next-generation sequencing (NGS) analysis, along with
in vitro
and
in vivo
assays, showed that GFP-McKrae virus was similar to WT-McKrae virus. Furthermore, corneal cells infected with GFP-McKrae were quantitatively analyzed using image mass cytometry (IMC). The single-cell reconstruction data generated cellular maps of corneas based on the expression of 25 immune cell markers in GFP-McKrae-infected mice. Corneas from mock control mice showed the presence of T cells and macrophages, whereas corneas from GFP-McKrae-infected mice on days 3 and 5 post-infection (PI) exhibited increased immune cells. Notably, on day 3 PI, increased GFP expression was observed in closely situated clusters of DCs, macrophages, and epithelial cells. By day 5 PI, macrophages and T cells became prominent. Finally, immunostaining methods detected HSV-1 or GFP and gD proteins in latently infected TG. This study presents a valuable strategy for identifying cellular spatial associations in viral pathogenesis and holds promise for future therapeutic applications.

IMPORTANCE
The goal of this study was to establish quantitative approaches to analyze immune cell markers in HSV-1-infected intact corneas and trigeminal ganglia from primary and latently infected mice. This allowed us to define spatial and temporal interactions between specific immune cells and their potential roles in virus replication and latency. To accomplish this important goal, we took advantage of the utility of GFP-McKrae virus as a valuable research tool while also highlighting its potential to uncover previously unrecognized cell types that play pivotal roles in HSV-1 replication and latency. Such insights will pave the way for developing targeted therapeutic approaches to tackle HSV-1 infections more effectively.
Identification of reactive
Borrelia burgdorferi
peptides associated with Lyme disease
Authors: Tokarz Rafal , Guo Cheng , Sanchez-Vicente Santiago , Horn Elizabeth , Eschman Aleah , Turk Siu Ping , Lipkin W. Ian , Marques Adriana 
Published: September 2024

ABSTRACT

Borrelia burgdorferi,
the agent of Lyme disease, is estimated to cause >400,000 annual infections in the United States. Serology is the primary laboratory method to support the diagnosis of Lyme disease, but current methods have intrinsic limitations that require alternative approaches or targets. We used a high-density peptide array that contains >90,000 short overlapping peptides to catalog immunoreactive linear epitopes from >60 primary antigens of
B. burgdorferi
. We then pursued a machine learning approach to identify immunoreactive peptide panels that provide optimal Lyme disease serodiagnosis and can differentiate antibody responses at various stages of disease. We examined 226 serum samples from the Lyme Biobank and the National Institutes of Health, which included sera from 110 individuals diagnosed with Lyme disease, 31 probable cases from symptomatic individuals, and 85 healthy controls. Cases were grouped based on disease stage and presentation and included individuals with early localized, early disseminated, and late Lyme disease. We identified a peptide panel originating from 14 different epitopes that differentiated cases versus controls, whereas another peptide panel built from 12 unique epitopes differentiated subjects with various disease manifestations. Our method demonstrated an improvement in
B. burgdorferi
antibody detection over the current two-tiered testing approach and confirmed the key diagnostic role of VlsE and FlaB antigens at all stages of Lyme disease. We also uncovered epitopes that triggered a temporal antibody response that was useful for differentiation of early and late disease. Our findings can be used to streamline serologic targets and improve antibody-based diagnosis of Lyme disease.

IMPORTANCE

Serology is the primary method of Lyme disease diagnosis, but this approach has limitations, particularly early in disease. Currently employed antibody detection assays can be improved by the identification of alternative immunodominant epitopes and the selection of optimal diagnostic targets. We employed high-density peptide arrays that enabled precise epitope mapping for a wide range of
B. burgdorferi
antigens. In combination with machine learning, this approach facilitated the selection of serologic targets early in disease and the identification of serological indicators associated with different manifestations of Lyme disease. This study provides insights into differential antibody responses during infection and outlines a new approach for improved serologic diagnosis of Lyme disease.
Draft genome sequences of three
Planktothrix rubescens
strains cultivated from a eutrophic lake in Norwalk, Ohio (USA)
Authors: Wagner Ryan S. , Bullerjahn George S. 
Published: September 2024

ABSTRACT

Draft genomes were generated for three filamentous toxin-producing cyanobacterial strains cultivated from aquatic sources in Ohio sequenced by NovaSeq S4. Here, we report the classification and genome statistics of
Planktothrix rubescens
PR221, PR222, and PR223.
EasyAsk: An In-App Contextual Tutorial Search Assistant for Older Adults with Voice and Touch Inputs
Authors: Gao Weiwei , Du Kexin , Luo Yujia , Shi Weinan , Yu Chun , Shi Yuanchun 
Published: September 2024

An easily accessible tutorial is crucial for older adults to use mobile applications (apps) on smartphones. However, older adults often struggle to search for tutorials independently and efficiently. Through a formative study, we investigated the demands of older adults in seeking assistance and identified patterns of older adults' behaviors and verbal questions when seeking help for smartphone-related issues.
Informed by the findings from the formative study, we designed EasyAsk, an app-independent method to make tutorial search accessible for older adults. This method was implemented as an Android app. Using EasyAsk, older adults can obtain interactive tutorials through voice and touch whenever they encounter problems using smartphones. To power the method, EasyAsk uses a large language model to process the voice text and contextual information provided by older adults, and another large language model to search for the tutorial. Our user experiment, involving 18 older participants, demonstrated that EasyAsk helped users obtain tutorials correctly in 98.94% of cases, making tutorial search accessible and natural.
RDGait: A mmWave Based Gait User Recognition System for Complex Indoor Environments Using Single-chip Radar
Authors: Wang Dequan , Zhang Xinran , Wang Kai , Wang Lingyu , Fan Xiaoran , Zhang Yanyong 
Published: September 2024

In this paper, we aim to study millimeter-wave-based gait recognition in complex indoor environments, focusing on dealing with multipath ghosts and supporting rapid deployment to new environments. We design a ghost detection algorithm based on velocity change patterns. This algorithm relies solely on velocity estimation, requiring no environmental priors or multipath modeling. Hence, it is suitable for single-chip millimeter-wave radar with low angular resolution and can be conveniently deployed in new indoor settings. In addition, we build a gait recognition network based on an attention-based Recurrent Neural Network (RNN) to extract spatiotemporal-velocity features from RD heatmaps.
We have evaluated RDGait in two scenarios: a corridor scenario and a crowded office scenario, with 125 volunteers of different genders and ages ranging from 6 to 63. RDGait achieves a user recognition accuracy exceeding 95% among 125 candidates in both scenarios. We have further deployed RDGait in two additional scenarios using the pretrain-finetune approach. With minimal user registration data, RDGait could achieve satisfactory (> 90%) recognition accuracy in these new environments considering different radar placements, heights, and number of co-existing users.
From a Spoke to a Hub: The Case of South Korea
Authors: Lee Woocheol 
Published: September 2024

A few East Asian newly industrialized countries that used to belong to the Global South not only have joined the Global North but also have organized their own production chains in specific industries. Given the imperialist and exploitative nature of global production chains established by the Global North, it should be questioned whether the production chains organized by the East Asian newly industrialized countries are free from the innate nature of production chains. This article adopts a multiregional input-output analysis to examine the bilateral trade relationship between Korea and Vietnam. It finds that the Korean economy has unequally captured the benefits from the bilateral trade with Vietnam in terms of the domestic value-added share and the spillover effect derived from the final demand for Vietnamese products in the textile and electronics industries. JEL Classification: F62, F63
Reporting Hormone Receptor Expression in Breast Carcinomas: Which Method has the Highest Prognostic Power and What Should be the Optimal Cut-off Value?
Authors: Öztürk Çiğdem , Okcu Oğuzhan , Öztürk Seda Duman , Şen Bayram , Öztürk Ahmet Emin , Bedir Recep 
Published: September 2024

. Hormone receptor (HR) expression is a critical marker that plays a role in the treatment and management of breast cancer. Even if patients receive hormone treatment with a hormone positivity rate of over 1%, it is controversial at what level of positivity they benefit from treatment and contribute positively to their prognosis. . We retrospectively examined the estrogen receptor (ER) / progesterone receptor (PR) expression status, clinicopathological findings, and survival data of 386 patients who underwent surgery for breast cancer. ER/PR expressions of the patients were evaluated according to Allred, H-score and were also grouped according to staining percentages. Separate cut-off values were determined for each of these evaluation methods, and the prognostic power of these methods was investigated using receiver operating characteristic analysis. . The prognostic power of all methods was found to be similar in terms of predicting survival. According to the staining percentage of the patients, survival was excellent if the ER value was >80% and the PR value was >1%. . All recommended methods for reporting HRs have similar prognostic power. However, in patients with high percentage staining for ER using these methods, the prognosis is excellent. As a result, we predict that if the percentage of ER staining is low, changing the treatment management of patients may be considered clinically.