bluuebunny/crossref_metadata_2025_split huggingface dataset:
Earthquake response prediction of seismically isolated buildings based on the response spectrum method considering changes in characteristics of lead rubber bearings due to repeated deformations
Authors: Kobayashi Masahito , Sato Keita , Sato Kazunori 
Published: August 2023

AbstractIn 2016, a countermeasure was announced against the Nankai Trough long‐period and long‐duration ground motions (LPGMs) in Japan. However, the response spectrum method (RSM), indicated by the Ministry of Construction notification Vol. 2009 (MCN), was out of the countermeasure. An RSM considering characteristic changes due to repeated deformations has also been proposed. However, since the damping correction formula of MCN was used, its applicability to LPMGs has not been sufficiently investigated. In this paper, a method is proposed to evaluate the influence of characteristic changes due to repeated deformations using RSM for LPGMs and seismically isolated buildings using the lead plug‐inserted laminated rubber (LRB).
Limitations of social prescribing to help prevent isolation and loneliness
Authors: Uchihira Takayuki , Nakajima Kazunori 
Published: August 2023

AbstractIn this study, a web‐based questionnaire was sent to residents of the Kinki region in the westside of Japan (N = 1053), and a multinomial logit analysis was conducted according to their isolation and loneliness status to examine social prescriptions that would presumably contribute to the prevention of isolation and loneliness. By comparing the marginal effects of social prescriptions on those with four types of isolation and loneliness status through the discrete choice model, we discovered that social prescriptions that contribute to the prevention of isolation and loneliness differ according to individuals by isolation and loneliness status. For example, for those who are not isolated but lonely, an effective strategy would be to encourage involvement in social contribution activities in the community and form high‐quality human relationships expecting to alleviate loneliness. The results also showed that residents in isolated situations tend to be indifferent to social contribution activities and social prescriptions to encourage involvement in such activities have limitations.
Understanding political polarization using language models: A dataset and method
Authors: Gode Samiran , Bare Supreeth , Raj Bhiksha , Yoo Hyungon 
Published: August 2023

AbstractOur paper aims to analyze political polarization in US political system using language models, and thereby help candidates make an informed decision. The availability of this information will help voters understand their candidates' views on the economy, healthcare, education, and other social issues. Our main contributions are a dataset extracted from Wikipedia that spans the past 120 years and a language model‐based method that helps analyze how polarized a candidate is. Our data are divided into two parts, background information and political information about a candidate, since our hypothesis is that the political views of a candidate should be based on reason and be independent of factors such as birthplace, alma mater, and so forth. We further split this data into four phases chronologically, to help understand if and how the polarization amongst candidates changes. This data has been cleaned to remove biases. To understand the polarization, we begin by showing results from some classical language models in Word2Vec and Doc2Vec. And then use more powerful techniques like the Longformer, a transformer‐based encoder, to assimilate more information and find the nearest neighbors of each candidate based on their political view and their background. The code and data for the project will be available here: “https://github.com/samirangode/Understanding_Polarization”
On safe and usable chatbots for promoting voter participation
Authors: Muppasani Bharath , Pallagani Vishal , Lakkaraju Kausik , Lei Shuge , Srivastava Biplav , Robertson Brett , Hickerson Andrea , Narayanan Vignesh 
Published: August 2023

AbstractChatbots, or bots for short, are multimodal collaborative assistants that can help people complete useful tasks. Usually, when chatbots are referenced in connection with elections, they often draw negative reactions due to the fear of mis‐information and hacking. Instead, in this work, we explore how chatbots may be used to promote voter participation in vulnerable segments of society like senior citizens and first‐time voters. In particular, we have built a system that amplifies official information while personalizing it to users' unique needs transparently (e.g., language, cognitive abilities, linguistic abilities). The uniqueness of this work are (a) a safe design where only responses that are grounded and traceable to an allowed source (e.g., official question/answer) will be answered via system's self‐awareness (metacognition), (b) a do‐not‐respond strategy that can handle customizable responses/deflection, and (c) a low‐programming design‐pattern based on the open‐source Rasa platform to generate chatbots quickly for any region. Our current prototypes use frequently asked questions (FAQ) election information for two US states that are low on an ease‐of‐voting scale, and have performed initial evaluations using focus groups with senior citizens. Our approach can be a win‐win for voters, election agencies trying to fulfill their mandate and democracy at large.
Cognitive determinants of decisional capacity in neurodegenerative disorders
Authors: Portley Makayla , Sherer Carolyn , Wu Tianxia , Farren Jennifer , Danielian Laura E. , Scholz Sonja W. , Traynor Bryan J. , Ward Michael E. , Haselhuhn Taryn , Snyder Allison , Kwan Justin Y. 
Published: August 2023

AbstractObjectiveCognitive contributions to decisional capacity are complex and not well understood. Capacity to consent for research has been linked to executive function, but executive function assessment tools are imperfect. In this study, we examine the relationship between decisional capacity and a newly developed executive function composite score and determine whether cognitive performance can predict impaired decisional capacity.MethodsThis is a cross sectional study of participants at the National Institutes of Health with frontotemporal dementia‐amyotrophic lateral sclerosis spectrum disorders enrolled between 2017 and 2022. A structured interview tool was used to ascertain research decisional capacity. Study participant Uniform Data Set (v3.0) executive function (UDS3‐EF) composite score, Clinical Dementia Rating Scale©, and Neuropsychiatric Inventory was determined.ResultsA decrease in UDS3‐EF composite score significantly increased the odds of impaired decisional capacity (OR = 2.92, 95% CI [1.66–5.13], p = 0.0002). Executive function was most impaired in frontotemporal dementia (−2.86, SD = 1.26) and least impaired in amyotrophic lateral sclerosis (−0.52, SD = 1.25) participants. The UDS3‐EF composite score was also strongly correlated to the Clinical Dementia Rating Scale©.InterpretationDecisional capacity is intrinsically related to executive function in neurodegenerative disorders, and executive dysfunction may predict a lack of decisional capacity alerting investigators of the need for additional scrutiny during the informed consent process.
Insulating Electrets Converted from Organic Semiconductor for High‐Performance Transistors, Memories, and Artificial Synapses
Authors: Li Dongfan , An Ning , Tan Kai , Ren Yurong , Wang Hong , Li Shengtao , Deng Qian , Song Jianwei , Bu Laju , Lu Guanghao 
Published: August 2023

AbstractElectrets are commonly used charged insulators that generate a quasi‐permanent electric field. However, when conventional electrets come into direct contact with semiconductors, the energy level mismatch at the interface results in low memory speed and high energy consumption of electret devices due to both charge injection and storage being non‐conducive. To address this, the n‐type semiconductor N,N′‐dioctyl‐3,4,9,10‐perylene tetracarboxylic diimide (C8‐PTCDI) is converted to C8‐PTCDI (D) via oxygen degradation. The resulting C8‐PTCDI (D) electrets, when charged using an electric field and/or light, retain the energy level of the n‐type semiconductors to facilitate charge trapping. They also exhibit deeper trap energy levels and increased trap density, thereby enhancing the sheet charge density of C8‐PTCDI (D) electrets (7.47 × 1012 cm−2). As a result, devices based on n‐type electrets demonstrate lower operation voltage (2 V) of transistors, lower operation voltage (20 V) of memories, and lower energy consumption (3.5 fJ per spike) of artificial synapses compared to those without n‐type electrets.
Carbon Dots‐Assisted Rapid Synthesis of Polypyrrole with High Uniformity for Efficient Solar‐Driven Water Evaporation
Authors: Ye Ziang , Zhang Yiqiang , Tian Zheyu , Chang Qing , Li Ning , Xue Chaorui , Hao Caihong , Yang Jinlong , Hu Shengliang 
Published: August 2023

AbstractSolar‐driven water evaporation is considered one of the most promising technologies to simultaneously address the energy crisis and freshwater scarcity. Developing efficient evaporators is highly sought after. Here, a strategy to realize the rapid polymerization of pyrrole and the uniform deposition of carbon dots‐polypyrrole (CDs‐PPy) on Balsa substrate is reported by using CDs solution obtained from the exfoliation of coal pitch with HCOOH/H2O2 as the trigger. This unreacted HCOOH/H2O2 in CDs solution, which gets well reused, can act as the oxidant to oxidize pyrrole, and also play a certain role in removing unstable hemicellulose from Balsa that produces more pores on cell walls. This method also avoids the formation of large PPy aggregates and enables CDs to be incorporated into the polymeric PPy. The obtained Balsa supported CDs‐PPy (CDs‐PPy/Balsa) with high uniformity well preserves the interconnected microporous structure of Balsa. Compared to Balsa supported PPy (PPy/Balsa) synthesized via the conventional polymerization method of pyrrole using ammonium persulfate as an oxidant in HCl aqueous medium, the obtained CDs‐PPy/Balsa evaporator with high physicochemical stability and salt resistance ability shows superior solar‐driven water evaporation performance. These favorable features can lead CDs‐PPy/Balsa to a greater use in practical solar‐driven water evaporation applications.
High‐Density Lipoprotein Engineering for Eye‐Drop Treatment of Age‐Related Macular Degeneration
Authors: Fukuda Ryosuke , Mahmuda Nargis , Kasirawat Sawangrat , Kawakami Ryo , Shima Rumina , Mizukami Yu , Shibukawa Shiori , Tada Yuki , Kawanishi Fumitake , Ogura Masatsune , Matsuki Kota , Nagai Yoshinori , Nakano Eri , Suda Kenji , Tsujikawa Akitaka , Murakami Tatsuya 
Published: August 2023

AbstractEye‐drop treatments of age‐related macular degeneration (AMD) are desirable; however, no clinically approved eye drop has been reported to date. This study aim to evaluate the therapeutic activity of eye‐drop instillation of a high‐density lipoprotein (HDL) variant bearing a cell‐penetrating peptide and neovasculature‐targeted peptide (AsnGlyArg [NGR] peptide) in a mouse model at a dose of 0.6–0.85 µg protein/eye drop. The results reveal that the activity of the abovementioned variant was >10‐fold higher than that of the previous variant lacking an NGR peptide. In addition, the anti‐inflammatory activity, cholesterol‐efflux capacity, and antiangiogenic activity of reconstituted HDL are significantly augmented by the attachment of these two peptides. The mechanism underlying this dramatic improvement is likely the expression of CD13, an NGR peptide receptor, on the cornea and conjunctiva in mice. CD13 mRNA/protein expression is also detected in cultured human corneal and conjunctival cells. These results demonstrate that NGR peptide is an unprecedented class of an absorption enhancer on the eye surface. Thus, HDL engineering is a potential strategy for developing eye drops to treat neovascular AMD by enhancing the ocular surface absorption and HDL functionalities.
Multifunctional Carbon Nanodot‐Based Advanced Diagnostics and Therapeutics
Authors: Kapat Kausik , Semwal Nitesh , Chillarge Anjali , Aswani Arja 
Published: August 2023

AbstractCarbon nanodots (CNDs) are an emerging class of zero dimensional (0D) carbon nanomaterials that accumulated immense interest from researchers in the past two decades due to their facile synthesis and unique photo‐physical and ‐chemical properties. In particular, their long wavelength fluorescence emission, enhanced tissue penetration depth, excellent water dispersibility, tunable surface chemistry, charge transfer properties, and biocompatibility have unveiled newer avenues for advanced application in therapeutics, diagnostics, theranostics, and tissue regeneration. The review typically emphasizes CNDs, excluding the other members of the carbon dots (CDs) family, which has not been covered before. After introducing CNDs in the carbon nanomaterial hierarchy, their synthesis, general properties, functionalization, and characterization are subsequently discussed. The following section elaborates on mechanisms of CNDs fluorescence, quenching, and associated factors based on the latest theories and models. The diagnostic, theranostic, and therapeutic applications of red/NIR‐emitting CNDs are thoroughly reviewed to cover the latest developments, including in vitro/in vivo bioimaging, thermoelectric and piezoelectric biosensing, and various soft and hard tissue regeneration. Overall, this work will enlighten passionate readers about the present status and futuristic aspects of CNDs in healthcare management, besides reported toxicities and challenges associated with their bench‐to‐bedside translation.
Recycled, Contaminated, Crumpled Aluminum Foil‐Driven Triboelectric Nanogenerator
Authors: Son Jin‐ho , Cha Kyunghwan , Chung Seh‐Hoon , Heo Deokjae , Kim Sunghan , Choi Moonhyun , Park In Soo , Hong Jinkee , Lee Sangmin 
Published: August 2023

AbstractWith rapid urbanization and global population growth, the amount of wasted aluminum foil is significantly increasing. Most deformed and contaminated foil is difficult to recycle; hence, it is landfilled or incinerated, causing environmental pollution. Therefore, using aluminum foil waste for electricity may be conducive to addressing environmental problems. In this regard, various literatures have explored the concept of energy generation using foil, while a crumple ball design for this purpose has not been studied. Thus, a recycled foil‐based crumpled ball triboelectric nanogenerator (RFCB‐TENG) is proposed. The crumpled ball design can minimize the effects of contamination on foil, ensuring efficient power output. Moreover, owing to novel crumpled design, the RFCB‐TENG has some outstanding characteristics to become a sustainable power source, such as ultralight weight, low noise, and high durability. By introducing the air‐breakdown model, the RFCB‐TENG achieved an output peak voltage of 648 V, a current of 8.1 mA cm3, and an optimum power of 162.7 mW cm3. The structure of the RFCB‐TENG is systemically optimized depending on the design parameters to realize the optimum output performance. Finally, the RFCB‐TENG operated 500 LEDs and 30‐W commercial lamps. This work paves the guideline for effectively fabricating the TENG using waste‐materials while exhibiting outstanding characteristics.
Surface Tension and Neuronal Sorting in Magnetically Engineered Brain‐Like Tissue
Authors: Perez Jose E. , Jan Audric , Villard Catherine , Wilhelm Claire 
Published: August 2023

AbstractEngineered 3D brain‐like models have advanced the understanding of neurological mechanisms and disease, yet their mechanical signature, while fundamental for brain function, remains understudied. The surface tension for instance controls brain development and is a marker of cell‐cell interactions. Here, 3D magnetic brain‐like tissue spheroids composed of intermixed primary glial and neuronal cells at different ratios are engineered. Remarkably, the two cell types self‐assemble into a functional tissue, with the sorting of the neuronal cells toward the periphery of the spheroids, whereas the glial cells constitute the core. The magnetic fingerprint of the spheroids then allows their deformation when placed under a magnetic field gradient, at a force equivalent to a 70 g increased gravity at the spheroid level. The tissue surface tension and elasticity can be directly inferred from the resulting deformation, revealing a transitional dependence on the glia/neuron ratio, with the surface tension of neuronal tissue being much lower. The results suggest an underlying mechanical contribution to the exclusion of the neurons toward the outer spheroid region, and depict the glia/neuron organization as a sophisticated mechanism that should in turn influence tissue development and homeostasis relevant in the neuroengineering field.
Printing Three‐Dimensional Refractory Metal Patterns in Ambient Air: Toward High Temperature Sensors
Authors: Yu Jichuan , Hu Chuxiong , Wang Ze , Wei Yuankong , Liu Zhijin , Li Qingang , Zhang Lei , Tan Qiulin , Zang Xining 
Published: August 2023

AbstractRefractory metals offer exceptional benefits for high temperature electronics including high‐temperature resistance, corrosion resistance and excellent mechanical strength, while their high melting temperature and poor processibility poses challenges to manufacturing. Here this work reports a direct ink writing and tar‐mediated laser sintering (DIW‐TMLS) technique to fabricate three‐dimensional (3D) refractory metal devices for high temperature applications. Metallic inks with high viscosity and enhanced light absorbance are designed by utilizing coal tar as binder. The printed patterns are sintered into oxidation‐free porous metallic structures using a low‐power (<10 W) laser in ambient environment, and 3D freestanding architectures can be rapidly fabricated by one step. Several applications are presented, including a fractal pattern‐based strain gauge, an electrically small antenna (ESA) patterned on a hemisphere, and a wireless temperature sensor that can work up to 350 °C and withstand burning flames. The DIW‐TMLS technique paves a viable route for rapid patterning of various metal materials with wide applicability, high flexibility, and 3D conformability, expanding the possibilities of harsh environment sensors.
Effect on water quality, growth performance and economics of giant freshwater prawn, Macrobrachium rosenbergii with partial feed in biofloc system
Authors: Islam Md. Amirul , Islam Shikder Saiful , Bir Joyanta , Debnath Prosenjit , Ullah Md. Rahamat , Huq Khandaker Anisul 
Published: August 2023

AbstractThe aim of the present study was to evaluate the water quality, growth performance, body composition, length–weight relationship, condition factors and benefit–cost analysis of giant freshwater prawn (Macrobrachium rosenbergii) cultured with biofloc system in pond conditions. The experiment was conducted in twelve (12) experimental ponds, each measuring 240 m2. The control group was cultured without any biofloc (T1), and biofloc‐based three treatments were biofloc with 100% feed (T2), biofloc with 90% feed (T3) and biofloc with 80% feed (T4). The biofloc‐based treatments showed significantly higher floc volume, total suspended solids, total heterotrophic bacteria and plankton density than the control (p < 0.05). All the growth parameters were significantly higher in biofloc‐based treatments (T2, T3 and T4) than in the control (T1). The lowest feed conversion ratio was found lowest in T4 (1.40 ± 0.02) and highest in T1 (2.13 ± 0.04), which was significantly different among the treatments (p < 0.05). The significantly highest production was obtained 939.02 ± 6.61 kg/ha in T2, and the lowest was 779.67 ± 7.50 kg/ha in T1. The length–weight relationship indicated positive allometric growth in all treatments. The condition factor ranged from 0.95 to 1.07, showing that the prawns were in good health throughout all treatments. The results of the present study indicated that M. rosenbergii can adapt to a biofloc‐based aquaculture system, and the conventional feeding rations can be reduced up to 20% without affecting the growth and production.
Food companies' productivity dynamics: Exploring the role of intangible assets
Authors: Nakatani Ryota 
Published: August 2023

AbstractFood insecurity has risen amid economic recovery from the COVID‐19 pandemic. Food companies' productivity dynamics can be driven by intangible assets, financing, economies of scale, lifecycle, and technological convergence. We confront this by studying productivity drivers for detailed food manufacturing industries using cross‐country firm‐level panel data. The results show that intangible assets nonlinearly and heterogeneously affect productivity growth, and countries with fewer product market regulations demonstrate higher productivity benefits from asset intangibility. Intangible assets do not play a major role for start‐up companies, while technological convergence drives productivity growth as they learn new technology in the food markets. Regarding the industrial differences, the bakery sector benefits the most from asset intangibility because of its brand images. Financing is particularly important for the meat/fish and dairy sectors, where capital equipment is necessary, and leverage effects are larger for countries with more access to financial institutions. Economies of scale are a vital productivity enhancer in the grain and starch sector for lowering fixed costs. Industrial policies to (i) raise the quality of intangible assets, (ii) promote financial access, and (iii) utilize scale economies are critical for improving the productivity of food manufacturers [EconLit Citations: D24, G32, L66, O34].
Numerical investigation of the reactive gas–solid characteristics in biomass fast pyrolysis of conical spouted reactor equipped with draft tube
Authors: Sun Haoran , Bao Guirong , Yang Shiliang , Hu Jianhang , Wang Hua 
Published: August 2023

AbstractBiomass fast pyrolysis is a promising technology to produce available char and high‐value gas due to its green and sustainable ability. In the current work, the biomass fast pyrolysis in draft tube spouted bed has been numerically investigated via the multiphase particle‐in‐cell model. In this model, gas turbulence is calculated via large eddy simulation and particles are individually tracked in the Lagrangian manner. This model is successfully validated against experimental data. The particle‐scale information of sand and biomass feedstock has been discussed, and the influence of draft tube configuration on the pyrolysis performance has been studied. The results show that the equipment of draft tube prevents gas leakage from spout to annulus, leading to large axial gas flux in the spout. Biomass particles in the spout and freeboard have high temperature and heat‐transfer coefficient. Some biomass particles move along the outer wall of draft tube, indicating that the equipment of draft tube can avoid back‐mixing by preventing direct contact of particles in the spout and annulus. Increasing the height of draft tube results in larger axial gas flux and higher sand heat‐transfer coefficient, while decreases biomass temperature in the spout. The simulation results can offer valuable insights into comprehending intricate reactive gas–solid characteristics and conducting operation and design optimization of spouting apparatus.