bluuebunny/crossref_metadata_2025 huggingface dataset:
Metal–insulator–metal micro-capacitors for integrated energy storage up to 105 Hz
Authors: Hourdakis E , Botzakaki M A , Xanthopoulos N J
Published: September 2022

Metal–insulator–metal (MIM) micro-capacitors for use in integrated energy storage applications are presented. A new, simple and batch Si processing compatible method for the creation of high aspect ratio metallic 3D structures on the surface of a Si substrate is described. The method consists of creating an array of Si nanopillars and then depositing Al at a small angle off the vertical while rotating the sample. Using this method, the effective area of the samples is increased by a factor of 3.8. Various capacitors are created using the described 3D structures as the lower electrode, with anodic alumina and atomic layer deposited HfO2 as the dielectric. Al and Cu top electrodes are also investigated. Large values of capacitance densities as high as 3.2 μF cm−2 are achieved. All capacitors are demonstrated to possess small values of series resistances and stable operation up to a frequency of 105 Hz. These results make the presented MIM capacitors exceed the state-of-the-art while maintaining a simple and integrable fabrication scheme which renders them very interesting for energy storage applications where operational frequencies larger than 1 kHz are required, as is the case in several vibrational energy harvesters.
Label-free ex vivo pathological studying on breast cancer tissue by using nonlinear multiphoton and micro-Raman spectral imaging
Authors: Xu Siyuan , Chen Xiwen , Ning Tian , Huang Xingxin , Chen Jianxin , Zhang Baoping , Chen Yishen , Wang Shuang
Published: September 2022

Raman spectral and multiphoton microscopy (MPM) were utilized in this study to understand the compositional and structural characteristics of the breast tumor microenvironment. Combining these techniques allowed us to address the pathological features of ex vivo healthy and invasive ductal carcinoma (IDC) breast tissue sections from different perspectives. MPM-based two-photon excited fluorescence and second-harmonic generation offer significant advantages for large-area structural tissue imaging. Raman spectral imaging identified the compositional information from a spectroscopic perspective and visualized the specific distribution patterns of biomedical components using a multivariate imaging method (K-mean cluster analysis, KCA). The MPM results revealed the loss of collagen bundles, malignant cell invasion, basement membrane damage, and blood vessel growth in IDC. Additionally, variations in tryptophan, nucleic acid, carotenoid, protein, and lipid content were found in different tissues. The reconstructed Raman images illustrate the morphological alterations of these contents and the edge contours of the cancerous tissue. The acquired multimodal optical results, which extracted complementary information of a sample based on different contrast mechanisms, provided new label-free pathological interpretations of the tumor microenvironment and offered the experimental foundations for developing multimode optical modalities as an immediate intraoperative diagnosis method.
Honeycomb lattice iridate on the verge of Mott-collapse
Authors: Haraguchi Yuya , Katori Hiroko Aruga
Published: September 2022

A new honeycomb lattice iridate (La,Na)IrO3 (≈LaNaIr2O6) is successfully synthesized from the spin–orbit coupled Mott insulator Na2IrO3 by replacing the interlayer Na+ ions with La3+ ions. (La,Na)IrO3 shows a finite Sommerfeld term in heat capacity and a −lnT dependence of resistivity, indicating a realization of a metallic state driven by a Mott collapse. Furthermore, crystal structure analysis reveals the formation of Ir zig-zag chains with metal–metal bonding, increasing kinetic energy resulting in the Mott collapse. This observation would be due to a Mott collapse induced in a J
eff = 1/2 spin–orbit coupling Mott insulator with an Ir honeycomb lattice by topochemical control of the ionic configuration.
Mechanical properties of 2D Zr
n

+1C
n
(n = 1, 2) MXenes with and without functionalization
Authors: Li Hengtao , Wang Hongyan , Li Xiumei , Li Yong , Chen Yuanzheng , Wang Hui
Published: September 2022

Transition metal carbides and nitrides (MXenes) are considered the new generation of flexible electronic materials because of their superior mechanical strength and flexibility. Based on the density functional theory, the structures, electronic properties and mechanical properties of the 2D Zr-based MXenes with and without surface functional groups (O, F and OH) are investigated systematically to explore their elastic properties and tensile fracture mechanism. The results reveal the tensile strength and critical strain under biaxial tensile direction can reach 52 GPa, 12% for Zr2C and 55 GPa, 19% for Zr3C2, more outstanding than the mechanical behavior of the pristine Ti2C (47 GPa, 9.5%). The tensile behaviors of the functionalized Zr
n

+1CnT2 (n = 1, 2, T = O, F, OH) strongly depend on the crystallographic orientation and the surface functional group. The phonon spectrum under the critical strain indicates the tensile fracture of the pristine Zr-based MXenes was determined by phonon instability, except along the armchair direction of Zr2C and zigzag direction of Zr3C2. During tensile strain, the collapse of Zr
n

+1C
n
F2 and Zr
n

+1C
n
(OH)2 (n = 1, 2) are mainly caused by internal Zr–C bond rupture and transfer to the surface. While the O-functionalized Zr
n

+1C
n
O2 (n = 1, 2) presented the opposite collapse trend. Additionally, according to the research results of critical strain, elastic modulus and electrical conductivity, F/OH-terminated Zr2C MXene is relatively more suitable for flexible sensors of wearable devices than Zr3C2T2.
An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring
Authors: Chamoin L , Farahbakhsh S , Poncelet M
Published: September 2022

This paper is a review on distributed optic fiber sensing for structural health monitoring applications, with a deeper focus on technologies relying on the Rayleigh backscattering phenomenon. It addresses the basic physical principles which are involved, the implementation and instrumentation of the measurement techniques, as well as recent practical applications, current performance, and remaining challenges. Being written at an elementary level and integrating relevant theoretical and technical details, we hope the document can be useful for researchers and engineers looking for an up-to-date overview on a field which currently undergoes significant development and increasing attractiveness, in particular for damage tracking in complex mechanical structures.
Black tea quality determination using a generic resistive gas sensor
Authors: Hosseini-Golgoo S M , Saeedi-Mirakmahaleh M , Saberi H
Published: September 2022

In this study, we present an analysis on the dynamic fermentation profile of a generic resistive gas sensor to optimize the process of turning green leaves into black tea and determine the quality of manufactured black tea, which are two crucial issues in the tea industry. The leaves were plucked from Lahijan and Rudsar, two important cultivation areas in Iran, in spring, summer and autumn. The results showed that the tea leaves optimum fermentation time (OFT) coincides with the second highest peak in the sensor’s dynamic fermentation profile. For example, various experiments showed that the second peak in the sensor’s dynamic response for the Lahijan summer tea samples, which had experienced optimal manufacturing stages, occurs in 117 ± 2 min. Also, tea tasters announced the OFT of 120 min for these samples by carefully examining five traits of the manufactured black tea. It was observed that the occurrence of this second peak is prolonged and even disappears as the quality of black tea decreases. To find the final black tea quality, we introduce a coordinate plane whose axes are determined based on the amplitude of the first peak and the occurrence of the second peak in the sensor’s dynamic fermentation profile. In this method, the characteristics of an optimal sample should be considered as a reference point. In the introduced classification space, the Euclidean distance of each point from the origin of the coordinates could also predict the tea taster’s score with a difference of ±0.5 marks. Finally, we show that the dynamic responses of a temperature-modulated gas sensor have sufficient discriminative features to segregate manufactured black tea samples based on their quality.
Multifunctional-high resolution imaging plate based on hydrophilic graphene for digital pathology
Authors: Lee Geonhee , Oh Yuna , Nam Jung Tae , Ji Seulgi , Jang A-Rang , Jeong Du Won , Kang MinSoung , Lee Sun Sook , Chae Soosang , Cho Donghwi , Hwang Jun Yeon , Lee Kyungeun , Lee Jeong-O
Published: September 2022

In the present study, we showed that hydrophilic graphene can serve as an ideal imaging plate for biological specimens. Graphene being a single-atom-thick semi-metal with low secondary electron emission, array tomography analysis of serial sections of biological specimens on a graphene substrate showed excellent image quality with improved z-axis resolution, without including any conductive surface coatings. However, the hydrophobic nature of graphene makes the placement of biological specimens difficult; graphene functionalized with polydimethylsiloxane oligomer was fabricated using a simple soft lithography technique and then processed with oxygen plasma to provide hydrophilic graphene with minimal damage to graphene. High-quality scanning electron microscopy images of biological specimens free from charging effects or distortion were obtained, and the optical transparency of graphene enabled fluorescence imaging of the specimen; high-resolution correlated electron and light microscopy analysis of the specimen became possible with the hydrophilic graphene plate.
OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines
Authors: Babier Aaron , Mahmood Rafid , Zhang Binghao , Alves Victor G L , Barragán-Montero Ana Maria , Beaudry Joel , Cardenas Carlos E , Chang Yankui , Chen Zijie , Chun Jaehee , Diaz Kelly , David Eraso Harold , Faustmann Erik , Gaj Sibaji , Gay Skylar , Gronberg Mary , Guo Bingqi , He Junjun , Heilemann Gerd , Hira Sanchit , Huang Yuliang , Ji Fuxin , Jiang Dashan , Carlo Jimenez Giraldo Jean , Lee Hoyeon , Lian Jun , Liu Shuolin , Liu Keng-Chi , Marrugo José , Miki Kentaro , Nakamura Kunio , Netherton Tucker , Nguyen Dan , Nourzadeh Hamidreza , Osman Alexander F I , Peng Zhao , Darío Quinto Muñoz José , Ramsl Christian , Joo Rhee Dong , David Rodriguez Juan , Shan Hongming , Siebers Jeffrey V , Soomro Mumtaz H , Sun Kay , Usuga Hoyos Andrés , Valderrama Carlos , Verbeek Rob , Wang Enpei , Willems Siri , Wu Qi , Xu Xuanang , Yang Sen , Yuan Lulin , Zhu Simeng , Zimmermann Lukas , Moore Kevin L , Purdie Thomas G , McNiven Andrea L , Chan Timothy C Y
Published: September 2022

Objective. To establish an open framework for developing plan optimization models for knowledge-based planning (KBP). Approach. Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. Main results. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50–0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P < 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model. Significance. This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.
Automatic detection of primary and metastatic lesions on cervicothoracic region and whole-body bone using a uniform machine-learnable approach for [18F]-FDG-PET/CT image analysis
Authors: Nemoto Mitsutaka , Tanaka Atsuko , Kaida Hayato , Kimura Yuichi , Nagaoka Takashi , Yamada Takahiro , Hanaoka Kohei , Kitajima Kazuhiro , Tsuchitani Tatsuya , Ishii Kazunari
Published: September 2022

We propose a method to detect primary and metastatic lesions with Fluorine−18 fluorodeoxyglucose (FDG) accumulation in the lung field, neck, mediastinum, and bony regions on the FDG-PET/CT images. To search for systemic lesions, various anatomical structures must be considered. The proposed method is addressed by using an extraction process for anatomical regions and a uniform lesion detection approach. The uniform approach does not utilize processes that reflect any region-specific anatomical aspects but has a machine-learnable framework. Therefore, it can work as a lesion detection process for a specific anatomical region if it machine-learns the specific region data. In this study, three lesion detection processes for the whole-body bone region, lung field, or neck-mediastinum region are obtained. These detection processes include lesion candidate detection and false positive (FP) candidate elimination. The lesion candidate detection is based on a voxel anomaly detection with a one-class support vector machine. The FP candidate elimination is performed using an AdaBoost classifier ensemble. The image features used by the ensemble are selected sequentially during training and are optimal for candidate classification. Three-fold cross-validation was used to detect performance with the 54 diseased FDG-PET/CT images. The mean sensitivity for detecting primary and metastatic lesions at 3 FPs per case was 0.89 with a 0.10 standard deviation (SD) in the bone region, 0.80 with a 0.10 SD in the lung field, and 0.87 with a 0.10 SD in the neck region. The average areas under the ROC curve were 0.887 with a 0.125 SD for detecting bone metastases, 0.900 with a 0.063 SD for detecting pulmonary lesions, and 0.927 with a 0.035 SD for detecting the neck-mediastinum lesions. These detection performances indicate that the proposed method could be applied clinically. These results also show that the uniform approach has high versatility for providing various lesion detection processes.
XCIST—an open access x-ray/CT simulation toolkit
Authors: Wu Mingye , FitzGerald Paul , Zhang Jiayong , Segars W Paul , Yu Hengyong , Xu Yongshun , De Man Bruno
Published: September 2022

Objective. X-ray-based imaging modalities including mammography and computed tomography (CT) are widely used in cancer screening, diagnosis, staging, treatment planning, and therapy response monitoring. Over the past few decades, improvements to these modalities have resulted in substantially improved efficacy and efficiency, and substantially reduced radiation dose and cost. However, such improvements have evolved more slowly than would be ideal because lengthy preclinical and clinical evaluation is required. In many cases, new ideas cannot be evaluated due to the high cost of fabricating and testing prototypes. Wider availability of computer simulation tools could accelerate development of new imaging technologies. This paper introduces the development of a new open-access simulation environment for x-ray-based imaging. The main motivation of this work is to publicly distribute a fast but accurate ray-tracing x-ray and CT simulation tool along with realistic phantoms and 3D reconstruction capability, building on decades of developments in industry and academia. Approach. The x-ray-based Cancer Imaging Simulation Toolkit (XCIST) is developed in the context of cancer imaging, but can more broadly be applied. XCIST is physics-based, written in Python and C/C++, and currently consists of three major subsets: digital phantoms, the simulator itself (CatSim), and image reconstruction algorithms; planned future features include a fast dose-estimation tool and rigorous validation. To enable broad usage and to model and evaluate new technologies, XCIST is easily extendable by other researchers. To demonstrate XCIST’s ability to produce realistic images and to show the benefits of using XCIST for insight into the impact of separate physics effects on image quality, we present exemplary simulations by varying contributing factors such as noise and sampling. Main results. The capabilities and flexibility of XCIST are demonstrated, showing easy applicability to specific simulation problems. Geometric and x-ray attenuation accuracy are shown, as well as XCIST’s ability to model multiple scanner and protocol parameters, and to attribute fundamental image quality characteristics to specific parameters. Significance. This work represents an important first step toward the goal of creating an open-access platform for simulating existing and emerging x-ray-based imaging systems. While numerous simulation tools exist, we believe the combined XCIST toolset provides a unique advantage in terms of modeling capabilities versus ease of use and compute time. We publicly share this toolset to provide an environment for scientists to accelerate and improve the relevance of their research in x-ray and CT.
Adaptive margins for online adaptive radiotherapy
Authors: van der Bijl Erik , Remeijer Peter , Sonke Jan-Jakob , van der Heide Uulke A , Janssen Tomas
Published: September 2022

Objective. In online adaptive radiotherapy a new plan is generated every fraction based on the organ and clinical target volume (CTV) delineations of that fraction. This allows for a planning target volume margin that does not need to be constant over the whole course of treatment, as is the case in conventional radiotherapy. This work aims to introduce an approach to update the margins each fraction based on the per-patient treatment history and explore the potential benefits of such adaptive margins. Approach. We introduce a novel methodology to implement adaptive margins, isotropic and anisotropic, during a treatment course based on the accumulated dose to the CTV. We then simulate treatment histories for treatments delivered in up to 20 fractions using various choices for the standard deviations of the systematic and random errors and homogeneous and inhomogeneous dose distributions. The treatment-averaged adaptive margin was compared to standard constant margins. The change in the minimum dose delivered to the CTV was compared on a patient and a population level. All simulations were performed within the van Herk approach and its known limitations. Main results. The population mean treatment-averaged margins are down to 70% and 55% of the corresponding necessary constant margins for the isotropic and anisotropic approach. The reduction increases with longer fractionation schemes and an inhomogeneous target dose distribution. Most of the benefit can be attributed to the elimination of the effective systematic error over the course of treatment. Interpatient differences in treatment-averaged margins were largest for the isotropic margins. For the 10% of patients that would receive a lower than prescribed dose to the CTV this minimum dose to the CTV is increased using the adaptive margin approaches. Significance. Adaptive margins can allow to reduce margins in most patients without compromising patients with greater than average target motion.
Lamb wavefield-based monogenic signal processing for quantifying delamination in composite laminates
Authors: Sun Hu , Shao Weihan , Song Jiannan , Yang Xiaofeng , Wang Yishou , Qing Xinlin
Published: September 2022

Delamination is one of the common damages affecting the safety of composite structures. In this paper, a Lamb wavefield-based monogenic signal processing algorithm is proposed to quantify the delamination parameters in composite laminates, including location, size, shape, and depth. A quality-guided fast phase unwrapping algorithm is developed to solve the problem of phase wrapping after Riesz transform-based monogenic signal processing. Then, space distribution of the phase of Lamb wavefield can be extracted for calculating wavenumber distribution, which is related to the structural thickness or delamination depth and can be used for delamination imaging. Simulated Lamb wavefield signals calculated by finite element simulation are employed to evaluate the parameters of delamination in composite laminates. Compared with other traditional methods, the damage identification algorithm based on Riesz transform has excellent identification effect and shorter calculation time. The results show that the algorithm can be used not only for single delamination recognition but also for multi-delamination recognition with good accuracy. In particular, the interaction between incident waves along different ply directions and delamination is explored, and its influence on delamination quantification is studied, whose results are worthy of attention in engineering application. Finally, a completely non-contact laser ultrasonic system is established to obtain the Lamb wavefield with delamination. Experiments show that the algorithm can accurately quantify the location, size, shape, and depth of delamination.
Experimental evaluation of SMA-based multi-ring damping devices
Authors: Salehi Mohammad , Hodgson Darel , Parnell T Kim , DesRoches Reginald , Mild Edward
Published: September 2022

This paper investigates the performance of shape memory alloy (SMA)-based multi-ring (SBMR) damping devices through an extensive experimental program. SBMR devices were recently proposed for the seismic damage mitigation of building structures. These devices combine the shape recovery capability of austenitic NiTi rings with the high energy dissipation of a ring made of other metals, such as mild steel or martensitic NiTi, to achieve a balanced performance in terms of energy dissipation and self-centering. The experimental program consisted of two phases: (I) material testing, and (II) device testing. Phase I aimed at selecting the optimal heat treatments of austenitic and martensitic NiTi alloys for potential application in SBMR devices. To this end, 24 NiTi rod samples with various heat treatments were tested under uniaxial cyclic loading. With an optimal heat treatment, the residual strain of austenitic NiTi rods could be limited to less than 0.1% after 6% of elongation. In phase II, three rings made of austenitic NiTi, martensitic NiTi, and A36 steel, as well as a double-ring device and a triple-ring device, were tested under various bidirectional loading protocols. The test results showed that the austenitic NiTi ring with an optimized heat treatment could provide more than 93% of self-centering, but only less than 5% of effective damping ratio. However, both the double- and triple-ring devices provided at least 64% of self-centering and up to 16% of effective damping ratio. SBMR devices were also found capable of remaining usable after at least three strong seismic events with different durations.
Non-trivial band topology in the superconductor AuSn4: a first principle study
Authors: Karn N K , Sharma M M , Awana V P S
Published: September 2022

Topological semimetals such as Weyl or Dirac semimetal with superconductivity have emerged as a new class of topological materials to realize and study Majorana Fermion. This article reports the density functional theory calculated bulk electronic band structure of recently discovered topological superconductor candidate AuSn4. The study has been performed on AuSn4 considering two space groups symmetries viz. Aea2 and Ccce as reported earlier. This study is further extended to the calculation of Z2 invariants. The Fermi surfaces corresponding to the bands, which are responsible for non-trivial band topology along with the surface states are also mapped. The complete study suggests that AuSn4 is a topological semimetal. On AuSn4, it is the first report in the literature showing the non-trivial band topology based on first-principle calculations.
Electron correlations in the

Hc2

of Fe
y
Se

1−x

S
x
(0.10

⩽x⩽

0.24,

y⩾

0.9)
Authors: Wang Aifeng , Petrovic C
Published: September 2022

We report on the evolution of the electronic correlation strength across the nematic critical point in Fe
y
Se

1
−
x

S
x
(

0.10
⩽
x
⩽
0.24
;
y
⩾
0.9

), inferred from the measurements of the slope of the upper critical field

H

c
2

. Superconducting transition T

c
and quasiparticle mass

m
∗

exhibit similar reduction with sulfur content x. Our results indicate that electronic correlations from all Fermi surface pockets show strong interconnection with pairing strength and are not governed by the change of nematic fluctuations. The upper critical field anisotropy γ

H
=

H

c
2

a
b

/

H

c
2

c

exhibits a minimum in the critical region and stronger temperature dependence away from it.
Cosmological dependence of sterile neutrino dark matter with self-interacting neutrinos
Authors: Chichiri Carlos , Gelmini Graciela B. , Lu Philip , Takhistov Volodymyr
Published: September 2022

Unexplored interactions of neutrinos could be the key to understanding the nature of the dark matter (DM). In particular, active neutrinos with new self-interactions can produce keV-mass sterile neutrinos that account for the whole of the DM through the Dodelson-Widrow mechanism for a large range of active-sterile mixing values. This production typically occurs before Big-Bang Nucleosynthesis (BBN) in a yet uncharted era of the Universe.
 We assess how the mixing range for keV-mass sterile neutrino DM is affected by the uncertainty in the early Universe pre-BBN cosmology.
This is particularly relevant for identifying the viable parameter space of sterile neutrino searches allowed by all astrophysical limits, as well as for cosmology, since the detection of a sterile neutrino could constitute the first observation of a particle providing information about the pre-BBN epoch. We find that the combined uncertainties in the early Universe cosmology and neutrino interactions significantly expand the allowed parameter space for sterile neutrinos that can constitute the whole of the DM.
Generalized diffusion and random search processes
Authors: Zhou Tian , Trajanovski Pece , Xu Pengbo , Deng Weihua , Sandev Trifce , Kocarev Ljupco
Published: September 2022

We consider a one-dimensional Brownian search in the presence of trapping. The diffusion equation of the particle is represented by a memory kernel that enters the general waiting time probability density function. We find the general form of the first arrival time density, search reliability and efficiency and analyze several special cases of the memory kernel. We also analyze the Lévy search in the presence of trapping in cases of single and multiple targets, as well as combined Lévy–Brownian search strategies in case of a single target. The presented results are general and could be of interest for further investigation of different optimal search strategies, as well as in the animal foraging or spreading of contamination particles in the environment.
A model simulation of political segmentation through an estimation of the entropy
Authors: Domenikos George-Rafael , Mantzaris Alexander V
Published: September 2022

The interconnectivity of a global communication system has allowed exchanges of ideas and expression producing a plethora of positive results. There have also been notable exceptions where clashes of ideas produce friction between people and even violence in the effort to dominate a political discourse. Various models have been proposed on how these ideas arise, grow and interact with each other. This paper explores how the Schelling model of segregation can be modified to represent ideological states and from this new formulation is proposed to assess the entropic trajectory of its simulation. The simple yet expressive model proposed is modified where simulations are monitored from the entropic measures of the system based upon ideological interactions and movements. A key result is that the entropy displays spikes due to randomized outside influences, and that the total entropy of the system decreases. This provides insight into how a system of politically engaged agents can be monitored for stability.
Heat energy consumption forecast analysis: model-oriented multi-objective approach
Authors: Kutkarska R D , Koeva D Y
Published: September 2022

Forecasting the expected quantity of heat energy consumption by multiple residential buildings can be a time consuming task, if done manually. The energy consumption in a building can be represented as a data parameter that changes over a period of time. For forecasting purposes autoregressive models are most often used to analyse time series data. One solution of the problem is to perform a hyperparameter optimization and derive the best results according to a selected metric. However, the grid search approach is often a time-consuming and resource-intensive task requiring additional human interaction for the final assessment of the most suitable parameters. The purpose of this study is to explore the possibility of developing a fully automated software algorithm that will provide sufficient parameters for the prediction of heat energy using the seasonal autoregressive integrated moving average with exogenous variables model (SARIMAX).
Modelling and visualizing information entropy in Python
Authors: Petrov I
Published: September 2022

This paper examines the specifics of structural evolution in large systems and diverse distribution of resource in the context of the traditional Information Entropy concepts. An original and comprehensive methodology for modelling and visualizing the production of maximal and minimal levels of entropy is developed in Python/Pycharm environment.
Cold ironing feasibility study at the Heraklion Port
Authors: Karapidakis E , Nikolaidis E , Moraitakis G , Georgakis F , Papadakis M
Published: September 2022

Due to environmental considerations, ships are being required to turn off their generators while berthing and receive electric power from the shore. This method of electrical connection of ships to ports during berthing is called cold ironing. Cold ironing can significantly contribute to air quality improvement by mitigating harbours’ CO2, nitrogen oxygen and several harmful emissions. This study investigates the needs and assess the first steps of cold ironing implementation in the Port of Heraklion, while also discussing the relative energy mix of the island.
Development and testing of 37.8 MHz, 3.0 kW RF amplifier system for Radioactive Ion Beam facility at VECC Kolkata
Authors: Pandey H.K. , Jain A.K. , Mandi T.K. , Dutta D.P.
Published: September 2022

This paper reports the design, development and testing of a
3.0 kW, 37.8 MHz radio frequency (RF) amplifier system that has
been built by combining four solid-state amplifier modules of
1.0 kW each. The design philosophy and test results of individual
components such as driver amplifier, final amplifier modules, power
divider/combiner, dual directional coupler (DDC) with system control
and interlocks are discussed in detail. Compact 4-way Wilkinson
power divider and combiner have been implemented using combination
of 50 Ω coaxial cables at this lower frequency of
37.8 MHz. It provides better isolation between the ports and also
have high power handling capability. The amplifier has been tested
with existing 37.8 MHz quarter-wave resonator type re buncher in
the Radioactive Ion Beam (RIB) facility. The performance test
results of developed RF system with Re buncher cavity have been
presented in this report.
20th World Wind Energy Conference & Exhibition (WEEC 2022)
Authors: Astiaso Garcia D. , Lamagna L. , Gsänger S. , Martone S. , Rae P. , Reggiani R. , Togni S.
Published: September 2022

This paper represents a preface to the Proceedings of the 20th World Wind Energy Conference & Exhibition (WEEC 2022) held in Rimini, Italy, from the 28th to the 30th of June 2022. Background information, conference resolution and the organizational structure of the meeting, program committee, and acknowledgments of the contributions of the many people who made the conference a success are presented.
Wake interaction in offshore wind farms with mesoscale derived inflow condition and sea waves
Authors: Castorrini A. , Tieghi L. , Barnabei V.F. , Gentile S. , Bonfiglioli A. , Corsini A. , Rispoli F.
Published: September 2022

Numerical simulation is an indispensable tool for the design and optimization of wind farms layout and control strategies for energy loss reduction. Achieving consistent simulation results is strongly related to the definition of reliable weather and sea conditions, as well as the use of accurate computational fluid dynamics (CFD) models for the simulation of the wind turbines and wakes. Thus, we present a case study aiming to evaluate the wake-rotor interaction between offshore multi-MW wind turbines modelled using the Actuator Line Model (ALM) and realistic wind inflow conditions. In particular, the interaction between two DTU10 wind turbines is studied for two orientations of the upstream turbine rotor, simulating the use of a yaw-based wake control strategy. Realistic wind inflow conditions are obtained using a multi-scale approach, where the wind field is firstly computed using mesoscale numerical weather prediction (NWP). Then, the mesoscale vertical wind profile is used to define the wind velocity and turbulence boundary conditions for the high-fidelity CFD simulations. Sea waves motion is also imposed using a dynamic mesh approach to investigate the interaction between sea waves, surface boundary layer, and wind turbine wakes and loads.
Opportunities and challenges of energy performance contracting in the Italian market for energy efficiency services.
Authors: Mazzantini Silvano , Legge Annamaria Di , Mastracci Marco , Maurelli Patrick , Rosa Flavio
Published: September 2022

The improvement of energy efficiency entails important benefits both for the individual user, owner of the infrastructure, and for the community in general. In fact, Energy Efficiency is a strategic priority of the European Union. However, the great potential deriving from energy efficiency is currently untapped. The reason for this gap is essentially due to the reluctance of customers to commit financial resources for these projects. The EPC scheme allows to overcome this reluctance, offering the customer a wide range of services that exempt him from most of the risks and responsibilities associated with the implementation of the energy efficiency project. Nevertheless, a series of financial barriers hinder the application of EPCs, effectively limiting the use of a sophisticated contractual instrument, which could contribute to the development of the energy efficiency services market. This report examines the opportunity to encourage greater use of EPCs in Italy, using refinancing instruments.
Computational simulations reveal that Abl activity controls cohesiveness of actin networks in growth cones
Authors: Chandrasekaran Aravind , Clarke Akanni , McQueen Philip , Fang Hsiao Yu , Papoian Garegin A. , Giniger Edward
Published: September 2022

How do single-molecule dynamics produce multimicron-scale changes in actin organization in an extending axon? Comparison of computational simulations to in vivo data suggests that Abl kinase and Arp2/3 expand actomyosin networks by fragmenting them into multiple domains, thus toggling the axon between states of local versus global internal connectivity.
Impact of Changes to Concealed-Carry Weapons Laws on Fatal and Nonfatal Violent Crime, 1980–2019
Authors: Doucette Mitchell L , McCourt Alexander D , Crifasi Cassandra K , Webster Daniel W
Published: September 2022

The United States faces rapidly rising rates of violent crime committed with firearms. In this study, we sought to estimate the impact of changes to laws that regulate the concealed carrying of weapons (concealed-carry weapons (CCW) laws) on violent crimes committed with a firearm. We used augmented synthetic control models and random-effects meta-analyses to estimate state-specific effects and the average effect of adopting shall-issue CCW permitting laws on rates of 6 violent crimes: homicide with a gun, homicide by other means, aggravated assault with a gun, aggravated assault with a knife, robbery with a gun, and robbery with a knife. The average effects were stratified according to the presence or absence of several shall-issue permit provisions. Adoption of a shall-issue CCW law was associated with a 9.5% increase in rates of assault with a firearm during the first 10 years after law adoption and was associated with an 8.8% increase in rates of homicide by other means. When shall-issue laws allowed violent misdemeanants to acquire CCW permits, the laws were associated with higher rates of gun assaults. It is likely that adoption of shall-issue CCW laws has increased rates of nonfatal violent crime committed with firearms. Harmful effects of shall-issue laws are most clear when provisions intended to reduce risks associated with civilian gun-carrying are absent.
SpotLink enables sensitive and precise identification of site nonspecific cross-links at the proteome scale
Authors: Zhang Weijie , Gong Pengyun , Shan Yichu , Zhao Lili , Hu Hongke , Wei Qiushi , Liang Zhen , Liu Chao , Zhang Lihua , Zhang Yukui
Published: September 2022

Nonspecific cross-linker can provide distance restraints between surface residues of any type, which could be used to investigate protein structure construction and protein–protein interaction (PPI). However, the vast number of potential combinations of cross-linked residues or sites obtained with such a cross-linker makes the data challenging to analyze, especially for the proteome-wide applications. Here, we developed SpotLink software for identifying site nonspecific cross-links at the proteome scale. Contributed by the dual pointer dynamic pruning algorithm and the quality control of cross-linking sites, SpotLink identified > 3000 cross-links from human cell samples within a short period of days. We demonstrated that SpotLink outperformed other approaches in terms of sensitivity and precision on the datasets of the simulated succinimidyl 4,4′-azipentanoate dataset and the condensin complexes with known structures. In addition, some valuable PPI were discovered in the datasets of the condensin complexes and the HeLa dataset, indicating the unique identification advantages of site nonspecific cross-linking. These findings reinforce the importance of SpotLink as a fundamental characteristic of site nonspecific cross-linking technologies.
Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion
Authors: Huang Li , Zhang Li , Chen Xing
Published: September 2022

MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.
Clustering consistency with Dirichlet process mixtures
Authors: Ascolani F , Lijoi A , Rebaudo G , Zanella G
Published: September 2022

Dirichlet process mixtures are flexible nonparametric models, particularly suited to density estimation and probabilistic clustering. In this work we study the posterior distribution induced by Dirichlet process mixtures as the sample size increases, and more specifically focus on consistency for the unknown number of clusters when the observed data are generated from a finite mixture. Crucially, we consider the situation where a prior is placed on the concentration parameter of the underlying Dirichlet process. Previous findings in the literature suggest that Dirichlet process mixtures are typically not consistent for the number of clusters if the concentration parameter is held fixed and data come from a finite mixture. Here we show that consistency for the number of clusters can be achieved if the concentration parameter is adapted in a fully Bayesian way, as commonly done in practice. Our results are derived for data coming from a class of finite mixtures, with mild assumptions on the prior for the concentration parameter and for a variety of choices of likelihood kernels for the mixture.
Care Order Decisions—in the Domain of Social Work or the Courts? Social Workers’ Frontline Views
Authors: Enroos Rosi , Huhtanen Raija , Korpinen Johanna , Pösö Tarja , Välikoski Tuula-Riitta
Published: September 2022

This article examines social workers’ views on care order decisions in Finnish child welfare where the decision-making procedure takes place in either the social work or court domain depending on the parties’ consent or objection to the care order proposal. Exploring this parallel decision-making system provides insights into the less studied characteristics of non-adversarial decision-making compared with those of adversarial decision-making. Based on the interviews of twenty-nine social workers, the findings present a binary view of social workers: the court domain is mainly seen as being an arena for the legal safety for families whereas the social work domain is a psychosocial, fluent and smooth arena for making care order decisions important to family members. The study points out potential misuse of the social work domain. Additional safeguards are suggested to complement the existing legal, professional and ethical safeguards as well as the re-evaluation of the role and nature of consent as a divider of the decision-making procedures.
Local neuronal excitation and global inhibition during epileptic fast ripples in humans
Authors: Curot Jonathan , Barbeau Emmanuel , Despouy Elodie , Denuelle Marie , Sol Jean Christophe , Lotterie Jean-Albert , Valton Luc , Peyrache Adrien
Published: September 2022

Understanding the neuronal basis of epileptic activity is a major challenge in neurology. Cellular integration into larger scale networks is all the more challenging. In the local field potential, interictal epileptic discharges can be associated with fast ripples (200–600 Hz), which are a promising marker of the epileptogenic zone. Yet, how neuronal populations in the epileptogenic zone and in healthy tissue are affected by fast ripples remain unclear. Here, we used a novel ‘hybrid’ macro–micro depth electrode in nine drug-resistant epileptic patients, combining classic depth recording of local field potentials (macro-contacts) and two or three tetrodes (four micro-wires bundled together) enabling up to 15 neurons in local circuits to be simultaneously recorded. We characterized neuronal responses (190 single units) with the timing of fast ripples (2233 fast ripples) on the same hybrid and other electrodes that target other brain regions. Micro-wire recordings reveal signals that are not visible on macro-contacts. While fast ripples detected on the closest macro-contact to the tetrodes were always associated with fast ripples on the tetrodes, 82% of fast ripples detected on tetrodes were associated with detectable fast ripples on the nearest macro-contact. Moreover, neuronal recordings were taken in and outside the epileptogenic zone of implanted epileptic subjects and they revealed an interlay of excitation and inhibition across anatomical scales. While fast ripples were associated with increased neuronal activity in very local circuits only, they were followed by inhibition in large-scale networks (beyond the epileptogenic zone, even in healthy cortex). Neuronal responses to fast ripples were homogeneous in local networks but differed across brain areas. Similarly, post-fast ripple inhibition varied across recording locations and subjects and was shorter than typical inter-fast ripple intervals, suggesting that this inhibition is a fundamental refractory process for the networks. These findings demonstrate that fast ripples engage local and global networks, including healthy tissue, and point to network features that pave the way for new diagnostic and therapeutic strategies. They also reveal how even localized pathological brain dynamics can affect a broad range of cognitive functions.
Investigating form and content of emotional and non-emotional laughing
Authors: Lombardi Giada , Gerbella Marzio , Marchi Massimo , Sciutti Alessandra , Rizzolatti Giacomo , Di Cesare Giuseppe
Published: September 2022

As cold actions (i.e. actions devoid of an emotional content), also emotions are expressed with different vitality forms. For example, when an individual experiences a positive emotion, such as laughing as expression of happiness, this emotion can be conveyed to others by different intensities of face expressions and body postures. In the present study, we investigated whether the observation of emotions, expressed with different vitality forms, activates the same neural structures as those involved in cold action vitality forms processing. To this purpose, we carried out a functional magnetic resonance imaging study in which participants were tested in 2 conditions: emotional and non-emotional laughing both conveying different vitality forms. There are 3 main results. First, the observation of emotional and non-emotional laughing conveying different vitality forms activates the insula. Second, the observation of emotional laughing activates a series of subcortical structures known to be related to emotions. Furthermore, a region of interest analysis carried out in these structures reveals a significant modulation of the blood-oxygen-leveldependent (BOLD) signal during the processing of different vitality forms exclusively in the right amygdala, right anterior thalamus/hypothalamus, and periaqueductal gray. Third, in a subsequent electromyography study, we found a correlation between the zygomatic muscles activity and BOLD signal in the right amygdala only.