bluuebunny/crossref_metadata_2025 huggingface dataset:
Serum microRNAs as new biomarkers for detecting subclinical hemolysis in the nonacute phase of G6PD deficiency
Authors: Boonpeng Kanyarat , Shibuta Tatsuki , Hirooka Yoshitaka , Kulkeaw Kasem , Palasuwan Duangdao , Umemura Tsukuru
Published: July 2024

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is one of the most common enzymopathies worldwide. Patients with G6PD deficiency are usually asymptomatic throughout their life but can develop acute hemolysis after exposure to free radicals or certain medications. Several studies have shown that serum miRNAs can be used as prognostic biomarkers in various types of hemolytic anemias. However, the impact of G6PD deficiency on circulating miRNA profiles is largely unknown. The present study aimed to assess the use of serum miRNAs as biomarkers for detecting hemolysis in the nonacute phase of G6PD deficiency. Patients with severe or moderate G6PD Viangchan (871G > A) deficiency and normal G6PD patients were enrolled in the present study. The biochemical hemolysis indices were normal in the three groups, while the levels of serum miR-451a, miR-16, and miR-155 were significantly increased in patients with severe G6PD deficiency. In addition, 3D analysis of a set of three miRNAs (miR-451a, miR-16, and miR-155) was able to differentiate G6PD-deficient individuals from healthy individuals, suggesting that these three miRNAs may serve as potential biomarkers for patients in the nonhemolytic phase of G6PD deficiency. In conclusion, miRNAs can be utilized as additional biomarkers to detect hemolysis in the nonacute phase of G6PD deficiency.
Activation of AMPD2 drives metabolic dysregulation and liver disease in mice with hereditary fructose intolerance
Authors: Andres-Hernando Ana , Orlicky David J. , Kuwabara Masanari , Fini Mehdi A. , Tolan Dean R. , Johnson Richard J. , Lanaspa Miguel A.
Published: July 2024

Hereditary fructose intolerance (HFI) is a painful and potentially lethal genetic disease caused by a mutation in aldolase B resulting in accumulation of fructose-1-phosphate (F1P). No cure exists for HFI and treatment is limited to avoid exposure to fructose and sugar. Using aldolase B deficient mice, here we identify a yet unrecognized metabolic event activated in HFI and associated with the progression of the disease. Besides the accumulation of F1P, here we show that the activation of the purine degradation pathway is a common feature in aldolase B deficient mice exposed to fructose. The purine degradation pathway is a metabolic route initiated by adenosine monophosphate deaminase 2 (AMPD2) that regulates overall energy balance. We demonstrate that very low amounts of fructose are sufficient to activate AMPD2 in these mice via a phosphate trap. While blocking AMPD2 do not impact F1P accumulation and the risk of hypoglycemia, its deletion in hepatocytes markedly improves the metabolic dysregulation induced by fructose and corrects fat and glycogen storage while significantly increasing the voluntary tolerance of these mice to fructose. In summary, we provide evidence for a critical pathway activated in HFI that could be targeted to improve the metabolic consequences associated with fructose consumption.
Sea ice choke points reduce the length of the shipping season in the Northwest Passage
Authors: Cook Alison J. , Dawson Jackie , Howell Stephen E. L. , Holloway Jean E. , Brady Mike
Published: July 2024

Arctic sea ice has shifted from a perennial (older, thicker ice) to a seasonal (younger, thinner) ice regime, leading to the increasingly common belief that shipping through Canada’s Northwest Passage is becoming more viable. Here, we use the Risk Index Outcome values derived from the Polar Operational Limit Assessment Risk Indexing System and analyze recent changes to shipping season lengths along individual sections of the Northwest Passage routes from 2007 to 2021. Results show that multi-year ice flushed southward from high-latitude regions maintains the so-called choke points along certain route sections, reducing overall shipping season length. There is considerable spatiotemporal variability in shipping season lengths along the southern and northern routes. Specifically, parts of the northern route exhibit a decrease of up to 14 weeks over the 15 years. The variability of shipping season and, in particular, the shortening of the season will impact not only international shipping but also resupply and the cost of food in many Arctic communities, which require a prompt policy response.
Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID
Authors: Hadley Emily , Yoo Yun Jae , Patel Saaya , Zhou Andrea , Laraway Bryan , Wong Rachel , Preiss Alexander , Chew Rob , Davis Hannah , Brannock M. Daniel , Chute Christopher G. , Pfaff Emily R. , Loomba Johanna , Haendel Melissa , Hill Elaine ,   N3C and RECOVER consortia, Moffitt Richard
Published: July 2024

Background

Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection.

Methods

We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. We calculate summary statistics, effect sizes, and Kaplan–Meier curves to better understand COVID-19 reinfections.

Results

Here we validate previous findings of reinfection incidence (6.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present findings that the proportion of Long COVID diagnoses is higher following initial infection than reinfection for infections in the same epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between initial infection and reinfection (chi-squared value: 25,697, p-value: <0.0001) with a medium effect size (Cramer’s V: 0.20, DoF = 3). Individuals who experienced severe initial and first reinfection were older in age and at a higher mortality risk than those who had mild initial infection and reinfection.

Conclusions

In a large patient cohort, we find that the severity of reinfection appears to be associated with the severity of initial infection and that Long COVID diagnoses appear to occur more often following initial infection than reinfection in the same epoch. Future research may build on these findings to better understand COVID-19 reinfections.
Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts
Authors: Zang Chengxi , Hou Yu , Schenck Edward J. , Xu Zhenxing , Zhang Yongkang , Xu Jie , Bian Jiang , Morozyuk Dmitry , Khullar Dhruv , Nordvig Anna S. , Shenkman Elizabeth A. , Rothman Russell L. , Block Jason P. , Lyman Kristin , Zhang Yiye , Varma Jay , Weiner Mark G. , Carton Thomas W. , Wang Fei , Kaushal Rainu
Published: July 2024

Background

SARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors.

Methods

In this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests.

Results

We observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7–0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6).

Conclusions

This observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.
The Ising model celebrates a century of interdisciplinary contributions
Authors: Macy Michael W. , Szymanski Boleslaw K. , Hołyst Janusz A.
Published: July 2024

The centennial of the Ising model marks a century of interdisciplinary contributions that extend well beyond ferromagnets, including the evolution of language, volatility in financial markets, mood swings, scientific collaboration, the persistence of unintended neighborhood segregation, and asymmetric hysteresis in political polarization. The puzzle is how anything could be learned about social life from a toy model of second order ferromagnetic phase transitions on a periodic network. Our answer points to Ising’s deeper contribution: a bottom-up modeling approach that explores phase transitions in population behavior that emerge spontaneously through the interplay of individual choices at the micro-level of interactions among network neighbors.
Effects of a semi-interpenetrating network hydrogel loaded with oridonin and DNase-I on the healing of chemoradiotherapy-induced oral mucositis
Authors: Pan Yuxue , Wang Mengyuan , Wang Peng , Wei Hongliang , Wei Xiangjuan , Wang Dongmei , Hao Yongwei , Wang Yongxue , Chen Hongli
Published: July 2024

Preparation of a drug-carrying semi-interpenetrating network hydrogel and investigation of its restorative effect on chemoradiotherapy-induced oral mucositis.
Locally boosted Li2S nucleation on VO2 by loading carbon quantum dots for soft-packaged lithium–sulfur pouch cells
Authors: Yang Ruoxuan , Zhang Yunfeng , Chen Xifang , Song Lixian , Hu Yue , Song Yingze
Published: July 2024

CQDs enhance the local electron/ion conductivity of VO2 and guarantee its adsorption efficiency. Accordingly, direct and large-yield Li2S nucleation is fulfilled on VO2/CQDs, leading to high cell energy density in soft-packaged Li–S pouch cells.
Aggregation-induced generation of circularly polarized luminescence in naphthaleneimide-based nanostructures with high dissymmetry factor
Authors: Likhar Aakash Ravikant , Cheran Arunima , Sengupta Alisha , Dutta Camelia , Kumar Jatish , Asthana Deepak
Published: July 2024

A self-assembly driven generation of circularly polarized luminescence (CPL) in aggregated as well as in solid state. The naphthaleneimide-based dyad system exhibits dissymmetry factors as high as 0.03 and 0.002 in aggregated and solid state, respectively.
Control of 3D oriented strain-induced natural rubber crystallites under spatial confinement: cellulose nanocrystal networks and thickness dependence
Authors: Wang Qiran , Song Yingkun , Zhang Qingsong , Su Juqiao , Liu Bin , Fu Lin , Yan Shouke , Hu Jian
Published: July 2024

3-Dimensional oriented strain-induced natural rubber (NR) crystallites can be formed by the network of cellulose nanocrystals (CNCs).
Isothermal and non-isothermal transport properties of diluted fullerene binary and ternary aromatic solvent mixtures
Authors: Errarte A. , Sommermann D. , Shevtsova V. , Köhler W. , Bou-Ali M. M.
Published: July 2024

Molecular diffusion, thermodiffusion and Soret coefficients of fullerene in aromatics and isomers are presented. Molecule displacement under isothermal and non-isothermal conditions is governed by molecular mass, density, viscosity or inertia moment.
Navigating the landscape of enzyme design: from molecular simulations to machine learning
Authors: Zhou Jiahui , Huang Meilan
Published: July 2024

Efficiently harnessing big data by combining molecular modelling and machine learning accelerates rational enzyme design for its applications in fine chemical synthesis and waste valorization, to address global environmental issues and sustainable development.
Controlled engineering of Bi4O5Br2 and BiOBr via interactions between imidazolium ionic liquids and medium during synthesis as a simple method for enhancement of photocatalytic activity
Authors: Bielicka-Giełdoń Aleksandra , Wilczewska Patrycja , Ślusarz Rafał , Terzyk Artur P. , Parnicka Patrycja , Szczodrowski Karol , Ryl Jacek , Qi Fei , Siedlecka E. M.
Published: July 2024

The synthesis of Bi4O5Br2 and BiOBr in non-polar (glycerol, ethylene glycol) and polar (0.1 M mannitol) solvents studied the impact of elongating alkyl side chains (C4mim+, C8mim+, C16mim+) of imidazolium ionic liquids on the materials' properties.
Inherent anti-Fenton property of single-atom rhenium for the ultra-durable oxygen reduction reaction
Authors: Yue Xin-Zheng , Liu Yun-Ce , Lu Bang-An , Du Xin , Lei Wen , Liu Zhong-Yi , Yi Sha-Sha , Lu Chao
Published: July 2024

We have created a Re-SAC catalyst featuring a Re–N4 configuration with inherent anti-Fenton properties during ORR catalytic activity.
Spiers Memorial Lecture: Quantum chemistry, classical heuristics, and quantum advantage
Authors: Chan Garnet Kin-Lic
Published: July 2024

We describe the problems of quantum chemistry, the intuition behind classical heuristic methods used to solve them, a conjectured form of the classical complexity of quantum chemistry problems, and the subsequent opportunities for quantum advantage.
Aloe polysaccharides ameliorate obesity-associated cognitive dysfunction in high-fat diet-fed mice by targeting the gut microbiota and intestinal barrier integrity
Authors: Mo Ling , Li Jingjing , Lu Hangsun , Lu Shaoda , Fu Henghui , Huang Bo , Zhao Chaochao
Published: July 2024

Aloe polysaccharides improve cognitive impairment in HF diet-induced mice, related to remodeling of the intestinal microbiota and changes in the intestinal barrier, in addition to improving inflammation and oxidative stress in the gut and brain.
A new scandium based catalyst for the green synthesis of polyols-polyesters starting from waste raw materials
Authors: Losito Onofrio , Veronico Lorenzo , De Cataldo Alessia , Casiello Michele , Fusco Caterina , Gentile Luigi , Mesto Ernesto , Schingaro Emanuela , D'Accolti Lucia
Published: July 2024

A new scandium-based catalyst was prepared under sustainable conditions, for the controlled synthesis of polyols-polyesters at low temperature and under solvent-free conditions.
Progress on fiber engineering for fabric innovation in ecological hydrophobic design and multifunctional applications
Authors: Li Wei , Yang Libing , Huang Jianying , Zheng Chan , Chen Yu , Li Yunbo , Yang Dapeng , Li Shuhui , Chen Zhong , Cai Weilong , Lai Yuekun
Published: July 2024

This review introduces the hydrophobic mechanism, natural materials and preparation strategies of green hydrophobic fabrics, and multi-functional textiles based on hydrophobic fabrics. The challenges and prospects in this field are also discussed.
A non-invasive approach for H2S gas sensing under stimulated breathing conditions: a kag-MOF based gas sensor as a case study
Authors: Zeama Mostafa , Jia Jiangtao , Zhou Sheng , Faleiros Murilo Calil , Yaqoob Usman , Shekhah Osama , Salama Khaled N. , Eddaoudi Mohamed
Published: July 2024

Herein we report the deployment of kag-MOF as a sensing layer on a capacitive IDE sensor for detecting H2S at room temperature.
Exploiting spirooxindoles for dual DNA targeting/CDK2 inhibition and simultaneous mitigation of oxidative stress towards selective NSCLC therapy; synthesis, evaluation, and molecular modelling studies
Authors: Islam Mohammad Shahidul , Al-Jassas Refaah M. , Al-Majid Abdullah Mohammed , Haukka Matti , Nafie Mohamed S. , Abu-Serie Marwa M. , Teleb Mohamed , El-Yazbi Amira , Alayyaf Abdul Majeed Abdullah , Barakat Assem , Shaaban Marwa M.
Published: July 2024

A new spirooxindole was designed, synthesized and characterized as dual DNA targeting/CDK2 inhibition and simultaneous mitigation of oxidative stress towards selective NSCLC therapy.
Sodium alginate-based coaxial fibers synergistically integrate moisture actuation, length tracing, humidity sensing, and electric heating
Authors: Dong Lizhong , Ren Ming , Wang Yulian , Yuan Xiaojie , Wang Xiaobo , Yang Guang , Li Yuxin , Li Wei , Shao Yunfeng , Qiao Guanlong , Li Weiwei , Sun Hongli , Di Jiangtao , Li Qingwen
Published: July 2024

A sodium alginate@MXene-based fiber prepared continuously enables the multifunctional synergy of moisture actuation, length tracing, humidity sensing, and electric heating.
Chemical and photothermal synergistic antimicrobial treatment for enhanced wound healing based on light/pH responsive nanocomposites
Authors: Gong Tao , Ma Qing , Qin Kaili , Wei Lingxi , Wen Chaochao , Zhu Huirui , Li Xiaoning , Chang Bingmei , Liang Wenting , Guo Rui
Published: July 2024

GO-LM-CD is anticipated to serve as a novel photothermal/pH-responsive nanocarrier for achieving efficient antibacterial effects through the synergistic interplay between photothermal materials and antibacterial drugs.
Vesicle-coacervate-driven efficient deposition of a sprayed droplet on hydrophobic soybean leaf surfaces
Authors: Zhang Zhipeng , Li Yixin , Liu Shuang , Li Junrong , Periyasami Govindasami , Li Haibing , Sun Yao
Published: July 2024

The inherent superhydrophobicity of a plant's leaves results in a low deposition efficiency of pesticides used to improve crop production.
Green synthesis of silver nanoparticles: understanding biological activities – anticancer, antimicrobial, and plasmid DNA cleavage properties through reactive oxygen species release
Authors: Shabulal Naseema Bee , Thiyagarajan Perumal , Albeshr Mohammed F. , Nagaraj Karuppiah , Velmurugan Gunasekaran , Maity Prasenjit , Mathivanan Isai , Abhijith S. M. , Lad Niyati Hemantkumar
Published: July 2024

Study on green-synthesized nanoparticles: preparation, characterization, biological effects, and DNA degradation capabilities confirmed through UV-visible and FTIR analysis.
Recycling of Li and Co from spent LiCoO2 cathode materials through a low-temperature urea-assisted sulfation roasting approach
Authors: Kong Yichuan , Duan Yongzhi , Zhang Yuezhi , Min Yulin , Lu Hongxiu , Shi Penghui
Published: July 2024

With the assistance of urea, ammonium sulfate roasting can be carried out more efficiently to convert spent LiCoO2 battery cathode materials into water-leachable substances for recycling.
Using non-adiabatic excitation transfer for signal transmission between molecular logic gates
Authors: Martynov A. I. , Belov A. S. , Nevolin V. K.
Published: July 2024

An excitonic circuit can be built from molecular logic gates with different types of orbital symmetry (ππ* and πσ*). There are no fundamental differences between ππ* → πσ* and ππ* → ππ* transitions for cases when an exciton hops between gates.
Theranostic nanogels: multifunctional agents for simultaneous therapeutic delivery and diagnostic imaging
Authors: Altinbasak Ismail , Alp Yasin , Sanyal Rana , Sanyal Amitav
Published: July 2024

Theranostic nanogels are indispensable modular platforms that enable a combined approach to therapy and diagnostics to address challenges in the treatment of complex and dynamic diseases such as cancer.
Controllable synthesis of hollow mesoporous organosilica nanoparticles with pyridine-2,6-bis-imidazolium frameworks for CO2 conversion
Authors: Anvarian-Asl Ghazale , Joudian Sadegh , Todisco Stefano , Mastrorilli Pietro , Khorasani Mojtaba
Published: July 2024

The effects of a hard template, stepwise addition of precursors, and Si/CTAB and organosilica/TEOS molar ratios have been systematically studied during the synthesis of hollow mesoporous organosilica nanoparticles with pyridine-bis-imidazolium units.
Aggregation-induced emission of azobenzene towards a sensitive indication on the self-assembly of a cellulose material
Authors: Gu Jingjing , Zhang Guoqiang , Chang Jiahao , Zhang Lei , Wu Zhongtao , Luo Xiliang , Wang Hao
Published: July 2024

The concentration of aggregates of a developed cellulose material in water could be regulated by light, resulting in a distinct fluorescence intensity change.
Well-defined nanomagnetic nitrilotriacetic acid complex of Cu(ii) supported on silica-coated nanosized magnetite: a new highly efficient and magnetically separable catalyst for C–N bond formation
Authors: Rajabzadeh Kimiya , Sardarian Ali Reza
Published: July 2024

Highly efficient catalyzed C–N bond formation by well-defined nitrilotriacetic acid Cu(ii) complex supported on silica coated nanosized magnetite as a novel magnetically separable catalyst.
MgAl-LDH nanoflowers as a novel sensing material for high-performance humidity sensing
Authors: Wang Luyu , Song Jia , Yu Chunyang
Published: July 2024

The novel QCM humidity sensor based on MgAl-LDH nanoflowers has superior humidity sensitivity and the ability to detect human respiration.
A stable and visualized fatty acid-based phase transition material constructed by solid-phase molecular self-assembly for thermal management
Authors: Ji Chunda , Huang Jianbin , Yan Yun
Published: July 2024

Stable and visualized fatty acid-based phase transition material.
A first-principles prediction of novel Janus ZrGeZ3H (Z = N, P, and As) monolayers: Raman active modes, piezoelectric responses, electronic properties, and carrier mobility
Authors: Vu Tuan V. , Vi Vo T. T. , Hiep Nguyen T. , Hoang Khanh V. , Kartamyshev A. I. , Phuc Huynh V. , Hieu Nguyen N.
Published: July 2024

In this article, an attempt is made to explore new materials for applications in piezoelectric and electronic devices.
Tuning the steric hindrance of alkylamines: a predictive model of steric editing of planar amines
Authors: Tomasini Michele , Voccia Maria , Caporaso Lucia , Szostak Michal , Poater Albert
Published: July 2024

Amines are one of the most prevalent functional groups in chemistry.
Understanding the gelation properties of the fluorophenyl glycosides of arabinoside gelators: experimental and theoretical studies
Authors: Pandey Sachchida N. , Pathak Navendu P. , Sengupta Arunava , Yadav Somnath
Published: July 2024

Incorporating fluorine atoms into the aryl ring of phenolic arabinosides renders them capable of gelating organic solvents. However, increasing the number of fluorine atoms is not always beneficial.
Benchmarking ionomers for CO2 electroreduction to multicarbon products in zero-gap electrolysers
Authors: Zeng Fan , Deng Huiying , Zhuansun Mengjiao , Teng Wenzhi , Wang Yuhang
Published: July 2024

This work benchmarks ionomers for CO2 electroreduction to multicarbon products. Ionomers with stronger hydrophobicity or having bulkier and less hydrated ionised side chains were found to favour *CO adsorption and multicarbon product formation.
Enhanced photoelectrochemical nitrogen reduction to ammonia by a plasmon-active Au grating decorated with the gC3N4@MoS2 heterosystem and plasmon-active nanoparticles
Authors: Zabelin Denis , Tulupova Anastasiia , Zabelina Anna , Tosovska Andrea , Valiev Rashid , Ramazanov Ruslan , Mares David , Jerabek Vitezslav , Burtsev Vasilii , Erzina Mariia , Michalcová Alena , Skvortsova Anastasiia , Svorcik Vaclav , Lyutakov Oleksiy
Published: July 2024

Coupled plasmon triggering significantly enhanced the NRR efficiency on the surface of semiconductor heterostructure (2D/2D) gC3N4@MoS2.
Long-wavelength photoresponsive gallium zinc oxynitride for efficient oxygen evolution and Z-scheme water splitting reactions
Authors: Iwasa Natsutogi , Sandaiji Hiroka , Nandy Swarnava , Nakabayashi Mamiko , Takata Tsuyoshi , Hisatomi Takashi , Domen Kazunari
Published: July 2024

Long-wavelength photoresponsive GaN:ZnO efficiently driving the oxygen evolution reaction expands the possibilities for effectively harnessing solar energy through water splitting.
Promoting your work to the materials community: editor top tips for writing an effective research paper
Authors: Augustyn Veronica , Cussen Serena A. , Kundu Subrata , Osterloh Frank E. , Unterlass Miriam M.
Published: July 2024

Writing an effective research paper is a special form of art. Read what the editors of J. Mater. Chem. A have to say about the topic.
Adaptive control of quadrotor suspended load systems with variable payload and wind disturbances
Authors: Wang Ruiying , Shen Jun , Qiu Hongling , Zhu Bohao
Published: July 2024

This paper introduces an adaptive control scheme for quadrotor suspended load systems, to track desired trajectory with variable payload and wind disturbances. The dynamic model of the quadrotor suspended load system is developed, taking into account the impact of the wind field described by the Dryden model. To attenuate the effects of payload variation and wind disturbances on the system, an adaptive control method based on disturbance observers is devised. Additionally, the uniform boundedness of all error signals is demonstrated. The effectiveness of the designed control method is verified through simulations, which serves to strengthen its applicability in practical applications.
Innovative hull cleaning robot design and control by Laguerre base model predictive control for impedance and vibration management
Authors: Madanipour Vahid , Najafi Farid
Published: July 2024

The intricate and unpredictable nature of underwater environments and disturbances necessitates the use of model predictive control for the effective operation and inspection of remotely operated vehicles (ROVs). This paper presented an innovative suspension system for a hull‐cleaning robot to control impedance while reducing the vibration of ROV brushes in the presence of environmental disturbances and uncertainties. The use of a model predictive controller that utilizes Laguerre functions results significant reduction in tracking time, and the efficiency of the proposed controller is demonstrated through successful impedance tracking in Z‐direction and vibration reduction in Z and Y directions of the robot in an uncertain environment with disturbance. A prototype robot is built and the controller performance is validated in a real condition and modal analysis theory output with experimental data. The results highlight the effectiveness of the designed suspension system and the developed MPC for real‐world applications where environmental conditions are unpredictable or subject to change while the robot is needed to clean the surface perfectly without scratching the hull.
Firing pattern manipulation of neuronal networks by deep unfolding‐based model predictive control
Authors: Aizawa Jumpei , Ogura Masaki , Shimono Masanori , Wakamiya Naoki
Published: July 2024

The complexity of neuronal networks, characterized by interconnected neurons, presents significant challenges in control due to their nonlinear and intricate behaviour. This paper introduces a novel method designed to generate control inputs for neuronal networks to regulate the firing patterns of modules within the network. This methodology is built upon temporal deep unfolding‐based model predictive control, a technique rooted in the deep unfolding method commonly used in wireless signal processing. To address the unique dynamics of neurons, such as zero gradients in firing times, the method employs approximations of input currents using a sigmoid function during its development. The effectiveness of this approach is validated through extensive numerical simulations. Furthermore, control experiments were conducted by reducing the number of input neurons to identify critical features for control. Various selection techniques were utilized to pinpoint key input neurons. These experiments shed light on the importance of specific input neurons in controlling module firing within neuronal networks. Thus, this study presents a tailored methodology for managing networked neurons, extends temporal deep unfolding‐based model predictive control to nonlinear systems with reset dynamics, and demonstrates its ability to achieve desired firing patterns in neuronal networks.
Emotion recognition in user‐generated videos with long‐range correlation‐aware network
Authors: Yi Yun , Zhou Jin , Wang Hanli , Tang Pengjie , Wang Min
Published: July 2024

Emotion recognition in user‐generated videos plays an essential role in affective computing. In general, visual information directly affects human emotions, so the visual modality is significant for emotion recognition. Most classic approaches mainly focus on local temporal information of videos, which potentially restricts their capacity to encode the correlation of long‐range context. To address this issue, a novel network is proposed to recognize emotions in videos. To be specific, a spatio‐temporal correlation‐aware block is designed to depict the long‐range correlations between input tokens, where the convolutional layers are used to learn the local correlations and the inter‐image cross‐attention is designed to learn the long‐range and spatio‐temporal correlations between input tokens. To generate diverse and challenging samples, a dual‐augmentation fusion layer is devised, which fuses each frame with its corresponding frame in the temporal domain. To produce rich video clips, a long‐range sampling layer is designed, which generates clips in a wide range of spatial and temporal domains. Extensive experiments are conducted on two challenging video emotion datasets, namely VideoEmotion‐8 and Ekman‐6. The experimental results demonstrate that the proposed method obtains better performance than baseline methods. Moreover, the proposed method achieves state‐of‐the‐art results on the two datasets. The source code of the proposed network is available at: https://github.com/JinChow/LRCANet.
Deep reinforcement learning and ant colony optimization supporting multi‐UGV path planning and task assignment in 3D environments
Authors: Jin Binghui , Sun Yang , Wu Wenjun , Gao Qiang , Si Pengbo
Published: July 2024

With the development of artificial intelligence, the application of unmanned ground vehicles (UGV) in outdoor hazardous scenarios has received more attention. However, the terrains in these environments are often complex and undulating, which also pose higher challenges to the multi‐UGV path planning and task assignment (MUPPTA) optimization. To efficiently improve the multi‐UGV collaboration in 3D environments, a MUPPTA method is proposed based on double deep Q learning network (DDQN) and ant colony optimization (ACO) to jointly optimize the path planning and task assignment decisions of multiple UGVs. The authors first comprehensively consider the characteristics of the 3D environments, and model the MUPPTA problem as a combinatorial optimization problem. To tackle it, the original problem is decomposed into the multi‐UGV path planning sub‐problem and task assignment sub‐problem, and solve them separately. First, the path planning sub‐problem in the 3D environments is transformed into a Markov decision process (MDP) model, and a multi‐UGV path planning algorithm based on DDQN (MUPP‐DDQN) is proposed to obtain the optimal paths and actual path costs between tasks through extensive offline learning and training. Based on this, a multi‐UGV task assignment algorithm is further proposed based on ACO (MUTA‐ACO) to solve the task assignment sub‐problem and achieve the optimal task assignment solution. Simulation results show that the proposed method is more cost‐effective and time‐saving compared to other comparison algorithms.
Research on integrated energy system planning based on the correlation between wind power and photovoltaic output
Authors: Zhang Xiaoming , Ding Chonglei , Liang Guangzhe , Yang Peihong , Wang Xiang
Published: July 2024

The research on the randomness and volatility of wind power (WP) and photovoltaic (PV) output of the integrated energy system (IES) has emerged as a pivotal concern, commonly dealt with by clustering techniques. However, traditional clustering techniques often fall short of capturing the comprehensive characteristics of the original scenery data. This paper presents an enhanced clustering logic to improve WP and PV output correlation scenarios. Utilizing the Frank‐Copula function, the complex relationship between WP and PV is accurately described. The Kendall rank correlation coefficient (Kendall′s tau) is used as a metric to study the correlation between these two renewable energy sources. The original scenes' correlation coefficients are then clustered using the K‐means algorithm, which forms the basis for scene reduction. On the basis, a two‐phase robust optimization method is employed to conduct a planning study for a real IES, with the total cost of the system as the optimal objective. This approach ensures that the planning results are better aligned with the specific local conditions during the operation cycle.
Sustainability qualification tool for Italian multi-family buildings
Authors: Buzzetti Michela , Del Pero Claudio , Oberti Ilaria
Published: July 2024

There is a growing interest in the real estate sector in tools for assessing the sustainability and quality of the building stock. Often such tools, regardless of their content but by their nature as an assurance tool, serve as a support and stimulus to the sustainable building market. This paper reports the steps and methodology followed in the development of a sustainability qualification system for condominium buildings. The structure of the system and its technical characteristics are described. The objective of the tool is to evaluate not only aspects related to the building’s construction and technical systems quality but also to highlight the ability to optimize condominium services and management practices.
Carbon emissions of cast-in-place and prefabricated buildings: A comparative analysis and carbon reduction strategy
Authors: Jiang Xiaoyan , Bai Xuemei
Published: July 2024

Prefabricated buildings are increasingly advocated for their benefits, which include a shortened construction period, cost-efficiency, and enhanced resource utilization. However, the comparison between prefabricated and cast-in-place buildings on life-cycle carbon emissions is still insufficient. This study assesses and analyses the life cycle carbon emission of both types of structures and achieves carbon reduction strategies at various life cycle stages from actual cases. The analysis reveals that for both modular and cast-in-place buildings, the materials contributing the most to carbon emissions are concrete blocks, concrete, steel rebar, formwork, and wall plaster. In addition, the formwork in prefabricated buildings constitutes nearly half of the total carbon emissions during the construction stage compared to cast-in-place structures. In the maintenance phase, cast-in-place buildings are more low-carbon than prefabricated buildings because the insulation can be replaced. During the dismantling stage, carbon emissions from prefabricated buildings are approximately 11.31% lower than those from cast-in-place structures. The study also introduces several carbon reduction measures, for example, substantial emission reductions can be attained by substituting ordinary Portland cement with new dry process cement, employing RRAC concrete over regular concrete, utilizing lightweight aggregate concrete blocks instead of aerated concrete blocks, and opting for recycled steel. Regarding the operational phase, the implementation of solar photovoltaic panels on building rooftops has been proven to effectively curtail carbon emissions.
Comparative assessment of the effects of furnace bottom ash and fly ash on mortar performance
Authors: Onaizi Ali M. , Tang Waiching
Published: July 2024

The increased reuse and recycling of industrial waste could significantly reduce resource footprint and greenhouse gas emissions. Furnace bottom ash (FBA) is a by-product of thermal power plants and recycling it in the construction industry could have substantial environmental and economic benefits. This study aimed to compare FBA-based mortar with that of FA as a partial substitute for cement in the production of sustainable mortar. Three mixtures with 10%, 20%, and 30% FBA were created, and their workability, compressive strength, and water absorption properties were examined. The workability of the mixtures decreased with an increase in the FBA percentage. The compressive strength of the FBA-containing mixtures was similar to the control mix at early ages, but as curing time increased, the strength of FBA-containing mortars increased considerably due to pozzolanic reactivity. Additionally, the FBA-containing mixes had lower water absorption than those containing fly ash (FA) and the control mixture. As the proportion of FBA in the mixture increased, the amount of water absorbed by the mortar cube decreased. The findings proposed that 10% is the optimal proportion of FBA to substitute cement, as it showed a comparable compressive strength to the control mixture at 7 and 28 days and surpassed the strength of the control sample by 14% after 56 days. This work is anticipated to pave the way to foster new research opportunities by enabling detailed comparisons between emerging and standardized cementitious materials. It will help minimize performance uncertainties and assist in incorporating emerging materials into those standards, enhancing their overall applicability and reliability.
Towards BIM-based digital twinning of BIPV(T)-façades
Authors: Edenhofner Fabian , Mandow Wael , Maier Theresa , Beyersdorffer Matthias , Zaun Anne , Rahnama Shervin , Lim Bianca , Giovannetti Federico , Mackenbach Sven , Klemt-Albert Katharina
Published: July 2024

The renewable energy technologies photovoltaic and solar heat play a major role for the decarbonizing of the building sector. Novel approaches show the integration of those energy systems in a building instead of the common rooftop installation. So-called Building-integrated Photovoltaic Thermal Systems (BIPV(T)) can e. g. act as a replacement for roofing or as façade. They grant the possibility of producing electricity as well as thermal energy. Due to the high significance of the operating phase of buildings in terms of general energy consumption and greenhouse gas emissions, the optimal operation of buildings and their technical systems plays a crucial role in set climate goals. Current trends in the digitalization of the construction world, such as Building Information Modeling (BIM) and Digital Twins, hold alleged potential for sustainable and forward-looking monitoring and maintenance processes of BIPV(T)-systems. This paper demonstrates a proof-of-concept towards a BIM-based digital twin for the yield monitoring and maintenance of an innovative BIPV(T)-façade. In addition to the basic concept, the realization of the prototype is discussed.
Examining the role of the superbonus 110% incentive in Italy through analyses of two residential buildings
Authors: Huerto-Cardenas Harold E. , Aste Niccolò , Buzzetti Michela , Del Pero Claudio , Leonforte Fabrizio , Miglioli Alessandro
Published: July 2024

Over the past few years, the Covid-19 pandemic has triggered an economic crisis, impacting various sectors including building construction. Within this sector, the residential section represents one of the main causes of energy consumption and pollutant emissions. To address this challenge the European Union has devised a strategic plan aimed at promoting energy efficiency and environmental sustainability, with a special focus on revitalizing the building sector. Within this strategic framework, the tax incentive Superbonus 110% introduced in 2020 has emerged as a pivotal program, incentivizing specific energy efficiency measures for existing buildings in alignment with the EU Directives. In this regard, this study aims to analyse the retrofit intervention of two existing residential buildings subsidized through the Superbonus 110% mechanism. A critical analysis of several passive and active energy efficiency measures is performed considering energy, environmental and economic indicators, employing a dynamic simulation approach. This work demonstrates how the proposed Italian funding program can enhance the diffusion of energy efficiency interventions. However, thanks to the analysis of real case studies, the criticalities and implications that such a mechanism has brought to the construction sector were highlighted, in the perspective of future incentives.
Sustainable development of human potential – is a strategic priority for ensuring national security of Country
Authors: Musagaliev Ajiniyaz , Gretchenko Anatoly , Gagarina Galina , Gorokhova Irina , Gretchenko Alexander
Published: July 2024

The article is a kind of response to the request of students of higher educational institutions majoring in “Economic Security”, who are faced with the need to assess the impact of sustainable human development on ensuring the national security of the state. In this context, the article, firstly, examines the theoretical aspects of human potential in the Russian national security system in the current geopolitical and financial-economic situation in the world. Secondly, the authors form a system of main indicators, highlighting among them those that characterize the level of development of education and science, as well as healthcare, and define methods for assessing the level of human development and its impact on the national economic security of the country. Thirdly, based on an analysis of identified threats in the fields of education, science and healthcare, ways to minimize them are proposed. Particular attention is paid to developing a forecast of selected indicators, which will help assess the development of human potential in the medium term, as well as formulate the necessary measures to reduce threats and increase economic security in this area.
Investing Solar Bifacial Half Cut Single PV Panel for Enriched Power Delivery and System Stability Using Hybrid Approaches
Authors: Venkatadurgaprasad Kante , Reddy Barry Venugopal , Varma Gadiraju Harish Kumar , Das Soumitra
Published: July 2024

Solar PV modules offer clean, renewable energy, reducing carbon footprint and lowering electricity costs. They provide energy independence and require low maintenance. However, previously adopted techniques like simple MPPT methods often struggled with efficiency under variable irradiance and partial shading conditions. These methods lacked adaptability and precision, leading to suboptimal power extraction and increased reliance on grid electricity. Advanced algorithms and better optimization techniques address these drawbacks by enhancing efficiency and responsiveness. A novel hybrid technique is introduced for maximizing the power output of Solar Bifacial Half cut single PV panels while ensuring consistent power flow within the system. These panels incorporate bifacial technology, capturing sunlight on both their front and rear surfaces, and utilize half-cut solar cells, dividing conventional cells into two smaller ones for increased efficiency and reduced losses, especially in shaded or non-uniform irradiance conditions. The proposed hybrid technique combines the Random Forest Algorithm (RFA) with the Osprey Algorithm (OA), enhancing the prediction accuracy of RFA. In order to maximise PV output power, this combined strategy known as RFA-OA focuses on continuously tracking the Maximum Power Point (MPP). Based on voltage and current parameters, the RFA-OA algorithm specifically calculates the precise duty cycles required for the PV's DC-DC converter under various shading situations. This control method minimises fluctuations in system parameters and outside disturbances to provide the best possible load demand satisfaction. The suggested approach is put into practice in the MATLAB/Simulink environment and contrasted with current practices. It achieves a remarkable maximum output power efficiency of 99.951% for the PV panel, showcasing its efficacy in maximizing power generation while maintaining system stability and reliability.
Enhancing Rotation in Quadruped Robots Using Multi-Degree- of-Freedom Tails
Authors: Rajkumar R. , Stephen Ponraj J. , Gowtham M. , Yathish Prasanna M. , Divakaran P.
Published: July 2024

The effects of a robotic tail's planar shape on a quadruped robot's ability to manipulate yaw angles are examined in this research. A quadruped model that takes ground contact friction into consideration is included in the simulation, along with tail structures that vary from a 1-degree of freedom (1 DOF) pendulum to a six-degree-of-freedom serpentine robot. To take advantage of the tail's motion and enhance net quadruped rotation, trajectories are generated utilizing split-cycle frequency modulation. In order to numerically investigate the effect of trajector parameters and tail assembly on the neted quadruped spin, quadruped and tail models are employed. The results demonstrate the value of a multi-DOF tail and stress the significance of centripetal and tangential loads on tail trajectory planning.
Nanomaterials in Tissue Engineering for Sustainable Healthcare Solutions
Authors: Singh Balpreet , Rawat Babita , Sidhu Jaspreet , Kumar Arvind , Sobti Sakshi , Prakash Akula , Sonia
Published: July 2024

Nanomaterials have become viable contenders in the field of tissue engineering, providing adaptable frameworks for long-lasting healthcare solutions. This work included the characterization of many types of nanoparticles, such as gold, silver, iron oxide, and quantum dots. The aim was to identify and understand their specific physicochemical features that are crucial for their use in tissue engineering. The gold nanoparticles had a diameter of 20 nm, a surface area of 30 m^2/g, and a positive zeta potential of +20 mV. In contrast, the silver nanoparticles had a smaller diameter of 15 nm, a surface area of 25 m^2/g, and a negative zeta potential of -15 mV. Iron oxide nanoparticles displayed a greater size of 30 nm, a higher surface area of 40 m^2/g, and a zeta potential of +10 mV. In contrast, quantum dots had the lowest size of 10 nm and a zeta potential of +30 mV. In addition, the characteristics of the scaffold, such as the size of its pores, its porosity, and its mechanical strength, were assessed. These features were shown to have a vital role in controlling how cells behave and in promoting tissue regeneration. The Poly(lactic-co-glycolic acid) (PLGA) scaffolds had a pore size of 100 µm, a porosity of 80%, and a mechanical strength of 20 MPa. In contrast, the collagen scaffolds had a smaller pore size of 50 µm, a greater porosity of 90%, and a lower mechanical strength of 15 MPa. The gelatin scaffolds had a pore size of 75 µm, a porosity of 85%, and a mechanical strength of 18 MPa. On the other hand, the chitosan scaffolds had a larger pore size of 120 µm, a porosity of 75%, and a higher mechanical strength of 25 MPa. Moreover, the assessment of cell survival and proliferation on scaffolds containing nanomaterials revealed their considerable influence on cellular behavior. Notably, gold nanoparticles exhibited the greatest cell viability rate of 95% and a substantial rise in cell proliferation. Finally, the drug release patterns from drug delivery systems based on nanomaterials demonstrated regulated and prolonged release kinetics, emphasizing its potential in improving therapeutic results. In summary, this work clarifies the many uses of nanomaterials in tissue engineering and emphasizes their importance in creating sustainable healthcare solutions.