bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protein plant factories: production and resource use efficiency of soybean proteins in vertical farming
Authors: Righini Isabella , Graamans Luuk , van Hoogdalem Mark , Carpineti Caterina , Hageraats Selwin , van Munnen Daniel , Elings Anne , de Jong Rick , Wang Shuna , Meinen Esther , Stanghellini Cecilia , Hemming Silke , Marcelis Leo FM 
Published: March 2024

AbstractBackgroundControlled environment agriculture, particularly vertical farms (VF), also called plant factories, is often claimed as a solution for global food security due to its ability to produce crops unaffected by weather or pests. In principle, essential macronutrients of the human diet, like protein, could technically be produced in VF. This aspect becomes relevant in the era of protein transition, marked by an increasing consumer interest in plant‐based protein and environmental challenges faced by conventional farming. However, the real question is: what does the cultivation of protein crops in VF imply in terms of resource use? To address this, a study was conducted using a VF experiment focusing on two soybean cultivars.ResultsWith a variable plant density to optimize area use, and because of the ability to have more crop cycles per year, protein yield per square metre of crop was about eight times higher than in the open field. Assuming soy as the only protein source in the diet, the resources needed to get total yearly protein requirement of a reference adult would be 20 m2of crop area, 2.4 m3of water and 16 MWh of electricity,versus164 m2, 111 m3and 0.009 MWh in the field.ConclusionsThe study's results inform the debate on protein production and the efficiency of VF compared to conventional methods. With current electricity prices, it is unlikely to justify production of simple protein crops in VF or promote it as a solution to meet global protein needs. © 2024 The Authors.Journal of The Science of Food and Agriculturepublished by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Gender Differences in Task Specific Dystonia: What Can we Learn from Musician's Dystonia?
Authors: Doll‐Lee Johanna , Passarotto Edoardo , Altenmüller Eckart , Lee André 
Published: March 2024

AbstractBackgroundMusician's Dystonia (MD) is a task specific, focal dystonia which usually occurs only at the instrument. The pathophysiology is not fully understood, but several risk factors like over‐practice and genetic predisposition are known. Interestingly, 80% of those affected are men, which stands in contrast to the gender distribution in other focal dystonias, such as cervical dystonia.ObjectivesOur aim was to evaluate the difference in women and men with regard to risk factors leading to MD.MethodsWe investigated known risk factors for MD in a large cohort of 364 MD patients by retrospectively collecting data on practice behavior and family history.ResultsIn line with previous studies, we found a ratio of ~4:1 men to women. Age at onset of MD was significantly lower in women; however, subsequent analysis revealed that it was a positive family history (FH+) and not gender that was associated with a lower age at onset. Furthermore, we found that those with negative family history had accumulated more practice time until onset of MD.ConclusionsThese results imply that the earlier age at onset in women did not depend on gender but was due to the higher proportion of a positive family history. In contrast, men were less likely to have a positive family history, suggesting that genetic factors may not be the primary reason for the higher prevalence of MD in men. Instead, differences in practice behaviors between men and women may contribute to this gender disparity.
Impact of Acute Dopamine Replacement on Cognitive Function in Parkinson's Disease
Authors: Seemiller Joseph , Morrow Christopher , Hinkle Jared T. , Perepezko Kate , Kamath Vidyulata , Pontone Gregory M. , Mills Kelly A. 
Published: March 2024

AbstractBackgroundPD causes striatal dopaminergic denervation in a posterior/dorsal to anterior/ventral gradient, leaving motor and associative cortico‐striato‐pallido‐thalamic loops differentially susceptible to hyperdopaminergic effects with treatment. As the choice and titration of symptomatic PD medications are guided primarily by motor symptoms, it is important to understand their cognitive implications.ObjectiveTo investigate the effects of acute dopaminergic medication administration on executive function in Parkinson's disease (PD).MethodsParticipants with idiopathic PD were administered the oral Symbol Digit Modalities Test (SDMT; n = 181) and the Stroop test (n = 172) in the off‐medication and “best on” medication states. ANCOVA was used to test for differences between off‐medication and on‐medication scores corrected for age and years of education.ResultsAfter administration of symptomatic medications, scores worsened on the SDMT (F = 11.70, P < 0.001, d = −0.13), improved on the Stroop color (F = 26.89, P < 0.001, d = 0.184), word (F = 6.25, P = 0.013, d = 0.09), and color‐word (F = 13.22, P < 0.001, d = 0.16) test components, and the Stroop difference and ratio‐based interference scores did not significantly change. Longer disease duration correlated with lower scores on the SDMT, Stroop color, word, and color‐word scores; however, longer disease duration and higher levodopa‐equivalents correlated with higher Stroop difference‐based interference scores.ConclusionsSymptomatic medication differentially affects performance on two cognitive tests in PD. After acute treatment, core Stroop measures improved, Stroop interference was unchanged, and SDMT performance worsened, likely reflecting complex changes in processing speed and executive function related to acute treatment. When considering motor symptom therapies in PD, an individual's cognitive demands and expectations, especially regarding executive function, should be considered.
Hyperpolarized 15N caffeine, a potential probe of liver function and perfusion
Authors: von Morze Cornelius , Shaw Ashley , Blazey Tyler 
Published: March 2024

AbstractPurposeTo demonstrate hyperpolarization of 15N‐caffeine and report exploratory findings as a potential probe of liver function and perfusion.MethodsAn amorphous formulation of [1,3‐15N2]caffeine was developed for hyperpolarization via dissolution dynamic nuclear polarization. Polarizer hardware was augmented to support monitoring of solid‐state 15N MR signals during the buildup of hyperpolarization. Liquid state hyperpolarized 15N MR signals were obtained in a preclinical 3T magnet by interfacing an external spectrometer console with home‐built RF surface coils. 15N signal decay constants were estimated in H2O and in vivo in liver and brain regions of rats at 3 T. Decays were also measured at 9.4 T to assess the effect of B0, and in the presence of albumin to assess the impact of protein binding.ResultsPolarization levels of 3.5% and aqueous T1 relaxation times of nearly 200 s were attained for both N1 and N3 positions at 3 T. Shorter apparent decay constants were observed in vivo, ranging from 25 s to 43 s, with modest extensions possible by exploiting competitive binding of iophenoxate with plasma albumin. Downstream products of caffeine could not be detected on in vivo 15N‐MR spectra of the liver region, even with metabolic stimulation by ‐naphthoflavone treatment. Considering the high perfusion rate of brain, persistence of caffeine signal in this region is consistent with potential value as a perfusion imaging agent.ConclusionThese results establish the feasibility of hyperpolarization of hyperpolarized 15N‐caffeine, but further work is necessary to establish the role of this new agent to probe liver metabolism and perfusion.
An extended phase graph‐based framework for DANTE‐SPACE simulations including physiological, temporal, and spatial variations
Authors: de Buck Matthijs H. S. , Jezzard Peter , Hess Aaron T. 
Published: March 2024

AbstractPurposeThe delay alternating with nutation for tailored excitation (DANTE)–sampling perfection with application‐optimized contrasts (SPACE) sequence facilitates 3D intracranial vessel wall imaging with simultaneous suppression of blood and CSF. However, the achieved image contrast depends closely on the selected sequence parameters, and the clinical use of the sequence is limited in vivo by observed signal variations in the vessel wall, CSF, and blood. This paper introduces a comprehensive DANTE‐SPACE simulation framework, with the aim of providing a better understanding of the underlying contrast mechanisms and facilitating improved parameter selection and contrast optimization.MethodsAn extended phase graph formalism was developed for efficient spin ensemble simulation of the DANTE‐SPACE sequence. Physiological processes such as pulsatile flow velocity variation, varying flow directions, intravoxel velocity variation, diffusion, and effects were included in the framework to represent the mechanisms behind the achieved signal levels accurately.ResultsIntravoxel velocity variation improved temporal stability and robustness against small velocity changes. Time‐varying pulsatile velocity variation affected CSF simulations, introducing periods of near‐zero velocity and partial rephasing. Inclusion of diffusion effects was found to substantially reduce the CSF signal. Blood flow trajectory variations had minor effects, but differences along the trajectory reduced DANTE efficiency in low‐ areas. Introducing low‐velocity pulsatility of both CSF and vessel wall helped explain the in vivo observed signal heterogeneity in both tissue types.ConclusionThe presented simulation framework facilitates a more comprehensive optimization of DANTE‐SPACE sequence parameters. Furthermore, the simulation framework helps to explain observed contrasts in acquired data.
High‐field downfield MR spectroscopic imaging in the human brain
Authors: Özdemir İpek , Etyemez Semra , Barker Peter B. 
Published: March 2024

AbstractPurposeTo investigate the feasibility of downfield MR spectroscopic imaging (DF‐MRSI) in the human brain at 7T.MethodsA 7T DF‐MRSI pulse sequence was implemented based on the previously described methodology at 3T, with 3D phase‐encoding, spectral‐spatial excitation, and frequency selective refocusing. Data were pre‐processed followed by analysis using the “LCModel” software package, and metabolite maps created from the LCModel results. Total scan time, including brain MRI and a water‐reference MRSI, was 24 min. The sequence was tested in 10 normal volunteers. Estimated metabolite levels and uncertainty values (Cramer Rao lower bounds, CRLBs) for nine downfield peaks were compared between seven different brain regions, anterior cingulate cortex (ACC), centrum semiovale (CSO), corpus callosum (CC), cerebellar vermis (CV), dorsolateral prefrontal cortex (DLPFC), posterior cingulate cortex (PCC), and thalamus (Thal).ResultsDF peaks were relatively uniformly distributed throughout the brain, with only a small number of peaks showing any significant regional variations. Most DF peaks had average CRLB<25% in most brain regions. Average SNR values were higher for the brain regions ACC and DLPFC (˜7 ± 0.95, mean ± SD) while in a range of 3.4–6.0 for other brain regions. Average linewidth (FWHM) values were greater than 35 Hz in the ACC, CV, and Thal, and 22 Hz in CC, CSO, DLPFC, and PCC.ConclusionHigh‐field DF‐MRSI is able to spatially map exchangeable protons in the human brain at high resolution and with near whole‐brain coverage in acceptable scan times, and in the future may be used to study metabolism of brain tumors or other neuropathological disorders.
TensorFit: A torch‐based tool for ultrafast metabolite fitting of large MRSI data sets
Authors: Turco Federico , Capiglioni Milena , Weng Guodong , Slotboom Johannes 
Published: March 2024

AbstractPurposeTo introduce a tool (TensorFit) for ultrafast and robust metabolite fitting of MRSI data based on Torch's auto‐differentiation and optimization framework.MethodsTensorFit was implemented in Python based on Torch's auto‐differentiation to fit individual metabolites in MRS spectra. The underlying time domain and/or frequency domain fitting model is based on a linear combination of metabolite spectroscopic response. The computational time efficiency and accuracy of TensorFit were tested on simulated and in vivo MRS data and compared against TDFDFit and QUEST.ResultsTensorFit demonstrates a significant improvement in computation speed, achieving a 165‐times acceleration compared with TDFDFit and 115 times against QUEST. TensorFit showed smaller percentual errors on simulated data compared with TDFDFit and QUEST. When tested on in vivo data, it performed similarly to TDFDFit with a 2% better fit in terms of mean squared error while obtaining a 169‐fold speedup.ConclusionTensorFit enables fast and robust metabolite fitting in large MRSI data sets compared with conventional metabolite fitting methods. This tool could boost the clinical applicability of large 3D MRSI by enabling the fitting of large MRSI data sets within computation times acceptable in a clinical environment.
Heuristic reoptimization of time‐extended multi‐robot task allocation problems
Authors: Bischoff Esther , Kohn Saskia , Hahn Daniela , Braun Christian , Rothfuß Simon , Hohmann Sören 
Published: March 2024

AbstractProviding high quality solutions is crucial when solving NP‐hard time‐extended multi‐robot task allocation (MRTA) problems. Reoptimization, that is, the concept of making use of a known solution to an optimization problem instance when the solution to a similar problem instance is sought, is a promising and rather new research field in this application domain. However, so far no approximative time‐extended MRTA solution approaches exist for which guarantees on the resulting solution's quality can be given. We investigate the reoptimization problems of inserting as well as deleting a task to/from a time‐extended MRTA problem instance. For both problems, we can give performance guarantees in the form of an upper bound of 2 on the resulting approximation ratio for all heuristics fulfilling a mild assumption. We furthermore introduce specific solution heuristics and prove that smaller and tight upper bounds on the approximation ratio can be given for these heuristics if only temporal unconstrained tasks and homogeneous groups of robots are considered. A conclusory evaluation of the reoptimization heuristic demonstrates a near‐to‐optimal performance in application.
Highly thermally conductive and EMI shielding composite fabricated via free‐radical polymerization of poly acrylic acid assisted by expanded graphite with liquid metal‐grafted MXene
Authors: Cho Jangwoo , Kim Jooheon 
Published: March 2024

AbstractPolymer composites offer numerous benefits, including low cost, easy processability, and diverse applications. In this work, we fabricated a composite material with high thermal conductivity and electromagnetic interference (EMI) shielding performance using EGaIn, a liquid metal (referred to as LM in this paper), MXene (MX), and expanded graphite (EG) as multifunctional fillers, along with polyacrylic acid (PAA). LM was used to exfoliate MX under the effect of shear force, which not only reduced the size of MX but also increased the aspect ratio of the 2D‐structured MX. MX was filled into the pores of EG to make a heat transfer path, thereby enhancing its thermal conductivity, mechanical properties, and EMI SE properties. LM served as the initiator of free‐radical polymerization to convert acrylic acid (AA) into PAA. Finally, the LMMX/EG/PAA composite was hot‐pressed to make the heat‐transfer path dense. As a result, the LMMX/EG/PAA composite exhibited a thermal conductivity of 1.88 W/m·K and an EMI shielding effect of 52 dB.
N‐DMBI Doping of Carbon Nanotube Yarns for Achieving High n‐Type Thermoelectric Power Factor and Figure of Merit
Authors: Suzuki Hiroo , Kametaka Jun , Nakahori Shinya , Tanaka Yuichiro , Iwahara Mizuki , Lin Haolu , Manzhos Sergei , Kyaw Aung Ko Ko , Nishikawa Takeshi , Hayashi Yasuhiko 
Published: March 2024

AbstractThe application of carbon nanotube (CNT) yarns as thermoelectric materials for harvesting energy from low‐grade waste heat including that generated by the human body, is attracting considerable attention. However, the lack of efficient n‐type CNT yarns hinders their practical implementation in thermoelectric devices. This study reports efficient n‐doping of CNT yarns, employing 4‐(1, 3‐dimethyl‐2, 3‐dihydro‐1H‐benzimidazole‐2‐yl) phenyl) dimethylamine (N‐DMBI) in alternative to conventional n‐dopants, with o‐dichlorobenzene emerging as the optimal solvent. The small molecular size of N‐DMBI enables highly efficient doping within a remarkably short duration (10 s) while ensuring prolonged stability in air and at high temperature (150 °C). Furthermore, Joule annealing of the yarns significantly improves the n‐doping efficiency. Consequently, thermoelectric power factors (PFs) of 2800, 2390, and 1534 µW m−1 K−2 are achieved at 200, 150, and 30 °C, respectively. The intercalation of N‐DMBI molecules significantly suppresses the thermal conductivity, resulting in the high figure of merit (ZT) of 1.69×10−2 at 100 °C. Additionally, a π‐type thermoelectric module is successfully demonstrated incorporating both p‐ and n‐doped CNT yarns. This study offers an efficient doping strategy for achieving CNT yarns with high thermoelectric performance, contributing to the realization of lightweight and mechanically flexible CNT‐based thermoelectric devices.
A modeling strategy for the shear and flexural performance prediction of SFRC beams without stirrups accounting for the variability of properties
Authors: Benedito André Vitor , Vanalli Leandro , Krahl Pablo Augusto , Martins Carlos Humberto , de Andrade Silva Flávio 
Published: March 2024

AbstractThe behavior of steel fiber reinforced concrete (SFRC) is highly dependent on mix design, where the properties of its components, such as cementitious matrix and fibers, impact the physical and mechanical properties of the composite. Incorporating steel fibers into concrete modifies its physical properties, potentially leading to fiber segregation and resulting in a nonuniform distribution of the fibers within the material. In experimental studies, an increase in fiber volume has been found to change the failure mode of SFRC beams from shear to flexure, and numerical investigations have shown that randomness in fiber distribution can significantly influence the behavior of the composite. Therefore, this study aims to develop a numerical model that considers variations in material properties to simulate the change in the failure mode of SFRC beams due to variations in fiber volume. The failure and yielding parameters were initially established and integrated into the concrete damaged plasticity (CDP). Subsequently, the response of both steel and concrete to tension or compression stresses was ascertained. Finally, the appropriate meshes and finite elements were chosen for the simulation. In the final approach, two methods were employed to introduce randomness into the beam. One divided the beam into different vertical segments: 30, 45, and 90, and the other combined vertical and horizontal segments: 30 vertical with 4 horizontal, 45 vertical with 5 horizontal, and 90 vertical with 10 horizontal. A script was developed in Python to automatically insert the properties. The numerical model successfully captured the change in failure mode from shear to flexure resulting from fiber volume increase. Vertical and horizontal segments increased toughness due to crack deviation, better predicting cracking pattern and loading capacity for the highest fiber contents.
Chemical study of the stem bark of Phyllanthus emblica (Phyllanthaceae)
Authors: Khoa Phan Thanh , Quy Pham Bao , Lien Do Thi My , Phung Nguyen Kim Phi , Tuyet Nguyen Thi Anh 
Published: March 2024

AbstractFrom the ethyl acetate extract of the stem bark of Phyllanthus emblica, a mixture of triterpene glycosides (1) and six compounds (2‐7) were isolated. The structure of these compounds were established as 3‐O‐α‐L‐arabinopyranosyloleanolic acid (1a), 3‐O‐α‐L‐arabinopyranosylursolic acid (1b), 16‐dehydropregnenolone (2), periplogenin (3), betulin (4), phyllanthol (5), gallic acid (6) and methyl gallate (7) by 1D, 2D NMR spectroscopies, and high resolution ESI‐MS analysis, as well as comparison with those reported in the literature. The compounds (1a), (1b), (2) and (3) were found for the first time from this genus.
Spinel‐layered Li2MnTiO4+z cathode material for Li‐ion batteries prepared by a sol‐gel method
Authors: Hung Vu Ngoc , Van‐Duong Dao , Trang Tran Thi 
Published: March 2024

AbstractHerein, the sol‐gel method is conducted to synthesize the spinel‐layered Li2MnTiO4+z (0.5LiMnTiO4•0.5Li2Mn0.5Ti0.5O3) nanoparticles as a cathode material for Li‐ion batteries. The structural and electrochemical properties of the material are investigated by means of X‐ray diffraction, scanning electron microscopy, electrochemical impedance spectroscopy, and charge‐discharge tests. The obtained sample shows a high capacity of 200 mAh g‐1 with a capacity retention of 90 % after 60 cycles at C/5.
Synthesis of furfural from Acacia mangium wood sawdust‐derived xylose by continuous distillation method using sulfonated carbonaceous catalyst from the same source
Authors: Chung Nguyen Hoang , Hoai Nguyen Thi Thu , Dien Le Quang 
Published: March 2024

AbstractIn this study, the hydrolysate containing ~15 g/L of xylose, which was obtained from Acacia mangium wood sawdust was used for the synthesis of xylose by a continuous distillation method. The synthesis was conducted at 150 °C for 7 h using a carbon‐based sulfonated catalyst (CBSC) from the same biomass source with an acid density of about 4.0 mmol/g. The CBSC showed its efficient catalytic activity in the dehydration of xylose to furfural. Under the optimal catalyst dosage of 20 wt% over xylose, the yield of furfural was 20.4 mol% and 34 wt% of xylose was transformed to furfural. The results presented a successful utilization of a wood‐derived solid acid catalyst for production of furfural from the same biomass source as a sustainable production of furans for biofuel additives.
Pyrolysis of cashew nut shell: A parametric study
Authors: Nam Nguyen Hong , Anh Khuong Duy , Truc Le Gia Thanh , Ha Truong An , Ha Vu Thi Thu 
Published: March 2024

AbstractCashew nut shell, a waste from cashew nut production, could become a potential biomass feedstock for gasification. In this study, a complete parametric study of cashew nut shell was conducted in pyrolysis conditions that are relevant to industrial processes. The effects of temperature, heating rate and residence time on the shrinkage, char yield, char energy, as well as characteristics of cashew nut shell (ash content, volatile matter, fixed carbon content, and heating value) have been deeply investigated. The study results suggest ideas for the development of advanced pyrolysis techniques to better control the char product characteristics, hence serving for multiple purposes, such as energy or activated carbon production.
Chemical constituents from the leaves of Styrax annamensis Guill
Authors: Tra Nguyen Thanh , Anh Tran Dang , Van Cuong Pham , Ha Nguyen Thi Thu , Anh Le Thi Tu , Cham Ba Thi , Son Ninh The 
Published: March 2024

AbstractA phytochemical study of the ethyl acetate extract (EtOAc) of Styrax annamensis leaves resulted in the isolation and determination of six known compounds, including three nor‐neolignans type 2‐phenylbenzofurans egonol (1), egonoic acid (2) and (–)‐machicendiol (3), two lignans styraxin (4) and vladinol D (5), and a triterpenoid pomolic acid (6). The chemical structures of these compounds were determined by NMR spectroscopies, and MS data. This is the first time to isolate these compounds from S. annamensis species. Compounds 3 and 5 have also been observed from genus Styrax for the first time.