bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantum Simulating the Electron Transport in Quantum Cascade Laser Structures
Authors: Trombettoni Andrea , Scazza Francesco , Minardi Francesco , Roati Giacomo , Cappelli Francesco , Consolino Luigi , Smerzi Augusto , De Natale Paolo 
Published: September 2021

AbstractUltracold fermionic atoms are proposed to be used in 1D optical lattices to quantum simulate the electronic transport in quantum cascade laser (QCL) structures. The competition between the coherent tunneling among (and within) the wells and the dissipative decay at the basis of lasing is discussed. In order to validate the proposed simulation scheme, such competition is quantitatively addressed in a simplified 1D model. The existence of optimal relationships between the model parameters is shown, maximizing the particle current, the population inversion (or their product), and the stimulated emission rate. This substantiates the concept of emulating the QCL operation mechanisms in cold‐atom optical lattice simulators, laying the groundwork for addressing open questions, such as the impact of electron–electron scattering and the origin of transport‐induced noise, in the design of new‐generation QCLs.
Bayesian modeling of location, scale, and shape parameters in skew‐normal regression models
Authors: Corrales Martha Lucía , Cepeda‐Cuervo Edilberto 
Published: September 2021

AbstractIn this paper, we propose Bayesian skew‐normal regression models where the location, scale and shape parameters follow (linear or nonlinear) regression structures, and the variable of interest follows the Azzalini skew‐normal distribution. A Bayesian method is developed to fit the proposed models, using working variables to build the kernel transition functions. To illustrate the performance of the proposed Bayesian method and application of the model to analyze statistical data, we present results of simulated studies and of the application to studies of forced displacement in Colombia.
Preparation of Ag/CdS/MIL‐101(Cr) Composite by Dual Solvent Method and Its Photocatalytic Hydrogen Production
Authors: Liu Fengjiao , Shan Xiaoyue , Gao Yan , Ju Li , Guan Rongfeng , Chi Xianhu 
Published: September 2021

AbstractMIL‐101(Cr) with regular octahedron structure was synthesized by hydrothermal method, and CdS/MIL‐101(Cr) was prepared by solution titration. CdS was introduced into the surface of MIL‐101(Cr) matrix with large surface area and its pores to make it well dispersed and grow. On this basis, nano‐Ag was compounded, and the charge transfer rate was increased and the optical response spectrum of CdS was prolonged by using the localized surface plasmon resonance effect of noble metals. The results showed that under visible light irradiation, Ag/CdS/MIL‐101(Cr)‐0.6 ternary composite exhibited excellent photocatalytic H2 generation rate (521.05 μmol/(g h), which was 1.9 times that of CdS/MIL‐101(Cr)‐0.4. This provides an idea for the synthesis of other high‐performance photocatalytic materials.
The Synergistic Character of Highly N‐Doped Coconut–Shell Activated Carbon for Efficient CO2 Capture
Authors: Rajasekaran Navvamani , Vinoba Mari , Al‐Sheeha Hanadi , Rana Mohan S. 
Published: September 2021

AbstractThe coconut shell‐based activated carbon (AC) surface was effectively anchored with amine moieties with acid treatment followed by tetraethylenepentamine (TEPA) anchoring. The activated carbon surface enhanced with basicity is likely to increase the sorbent properties towards CO2 adsorption. The AC surface was modified by varying TEPA concentrations. After amine doping, significant loss in textural property indicates their occupation inside the pores and surfaces. Further, the samples were thermally activated to retrieve the textural properties. The physicochemical properties of modified carbon were characterized using BET, TPD, FT‐IR, Raman spectroscopy and elemental composition. The amine‐modified and thermally activated carbons were tested for CO2 adsorption up to 25 bar at 25 °C. The acid‐base properties of N‐doped carbons were evaluated using isopropanol as a model test reaction at atmospheric pressure. The IPA reaction products of acetone and propene were quantified for their acid‐base nature and correlated to CO2 adsorption capacities. The CO2 adsorption capacity increases by tailoring synergistic properties between surface basicity and micropores. Hence, 20 % TEPA‐derived nitrogen‐enriched carbon reveals a higher yield of acetone 73 %, which in turn enhanced CO2 adsorption capacity of 9.9 mmol/g, and it is found to be a suitable applicant for CO2 capture.
Preparation of Macroporous High Adsorbent Resin and Its Application for Heavy Metal Ion Removal
Authors: Shi Changxin , Li Yuanze , Li Xinyue , Zhao Xiaohan , Ma Xintao , Zhou Xun , Cui Yuming , Ma Songmei , Xu Wenlong , Ren Chunguang 
Published: September 2021

AbstractMacroporous high adsorbent resins (MHAR) are important and urgent requirements for qualified adsorbents to remove toxic heavy metals in wastewater since the short adsorption time and large adsorption capacity. Herein, a new type of MHAR was prepared by graft copolymerization of acrylic acid with sodium carboxymethyl cellulose (CMC) and sodium alginate (SA) by using N, N′‐methylenebisacrylamide (MBA) as crosslinking agent, hydrogen peroxide (H2O2) and ascorbic acid as initiator. We characterized the morphology of the MHAR and explored the optimal conditions for MHAR to absorb water. The results showed that pH and temperature had great influences on the amount of heavy metals adsorption. The adsorption process is a linear model of multiphase multilayer molecular adsorption reaction, which belongs to the second‐level kinetic model. The adsorption thermodynamic experiment showed that the adsorption of Cu2+ by MHAR conforms to the Freundlich adsorption isotherm. This work succeeded in preparing a MHAR that may have potential applications in environmental governance.
Integrated, Highly Flexible, and Tailorable Thermoelectric Type Temperature Detectors Based on a Continuous Carbon Nanotube Fiber
Authors: Xia Xiaogang , Zhang Qiang , Zhou Wenbin , Mei Jie , Xiao Zhuojian , Xi Wei , Wang Yanchun , Xie Sishen , Zhou Weiya 
Published: September 2021

AbstractAs possible alternatives to traditional thermoelectric (TE) materials, carbon nanomaterials and their hybrid materials have great potential in the future application of flexible and lightweight temperature detection. In this work, an integrated, highly flexible, and tailorable TE temperature detector with high performance has been fabricated based on a continuous single‐walled carbon nanotube (SWCNT) fiber. The detector consists of more than one pairs of thermocouples composed of p‐type SWCNT fiber and n‐type SWCNT hybrid fiber in situ doped by polyethylenimine. Due to the node contact mechanism of the detection, the sensitivity of the detector can be improved with the increase of the number of p–n thermocouples, independent of the length of the thermocouple. The temperature detection process of the detector has been studied in detail. In particular, the integrated and flexible detector can be divided into several sub‐detectors easily by cutting, illustrating the prospect of large‐scale preparation of this kind of novel temperature detectors. Its high flexibility ensures the detector to maintain excellent detection performance after 15 000 bending circles. Furthermore, the as‐designed TE type temperature detector demonstrates a great application promise for real‐time temperature detection and temperature change sensing even in complex surface and harsh environment.
In situ establishment of Co/MoS2 heterostructures onto inverse opal‐structured N,S‐doped carbon hollow nanospheres: Interfacial and architectural dual engineering for efficient hydrogen evolution reaction
Authors: Lu Tingyu , Li Tongfei , Shi Desheng , Sun Jialin , Pang Huan , Xu Lin , Yang Jun , Tang Yawen 
Published: September 2021

AbstractRational design of low‐cost and high‐efficiency non‐precious metal‐based catalysts toward the hydrogen evolution reaction (HER) is of paramount significance for the sustainable development of the hydrogen economy. Interfacial manipulation‐induced electronic modulation represents a sophisticated strategy to enhance the intrinsic activity of a non‐precious electrocatalyst. Herein, we demonstrate the straightforward construction of Co/MoS2 hetero‐nanoparticles anchored on inverse opal‐structured N,S‐doped carbon hollow nanospheres with an ordered macroporous framework (denoted as Co/MoS2@N,S–CHNSs hereafter) via a template‐assisted method. Systematic experimental evidence and theoretical calculations reveal that the formation of Co/MoS2 heterojunctions can effectively modulate the electronic configuration of active sites and optimize the reaction pathways, remarkably boosting the intrinsic activity. Moreover, the inverse opal‐structured carbon substrate with an ordered porous framework is favorable to enlarge the accessible surface area and provide multidimensional mass transport channels, dramatically expediting the reaction kinetics. Thanks to the compositional synergy and structural superiority, the fabricated Co/MoS2@N,S–CHNSs exhibit excellent HER activity with a low overpotential of 105 mV to afford a current density of 10 mA/cm2. The rationale of interface manipulation and architectural design herein is anticipated to be inspirable for the future development of efficient and earth‐abundant electrocatalysts for a variety of energy conversion systems.
An Artificial Mechano‐Nociceptor with Mott Transition
Authors: Kumar Mohit , Park Ji‐Yong , Seo Hyungtak 
Published: September 2021

AbstractIntelligent touch sensing is now becoming an essential part of various human‐machine interactions and communication, including in touchpads, autonomous vehicles, and smart robotics. Usually, sensing of physical objects is enabled by applied force/pressure sensors; however, reported conventional tactile devices are not able to differentiate sharp and blunt objects, although sharp objects can cause unavoidable damage. Therefore, it is central issue to implement electronic devices that can classify sense of touch and simultaneously generate pain signals to avoid further potential damage from sharp objects. Here, concept of force‐enabled nociceptive behavior is proposed and demonstrated using vanadium oxide‐based artificial receptors. Specifically, versatile criteria of bio‐nociceptor like threshold, relaxation, no adaptation, allodynia, and hyperalgesia behaviors are triggered by pointed force, but the device does not mimic any of these by the force applied by blunt objects; thus, the proposed device classifies the intent of touch. Further, supported by finite element simulation, the nanoscale dynamic is unambiguously revealed by conductive atomic force microscopy and results are attributed to the point force‐triggered Mott transition, as also confirmed by temperature‐dependent measurements. The reported features open a new avenue for developing mechano‐nociceptors, which enable a high‐level of artificial intelligence within the device to classify physical touch.
Posits and the state of numerical representations in the age of exascale and edge computing
Authors: Poulos Alexandra , McKee Sally A. , Calhoun Jon C. 
Published: September 2021

AbstractGrowing constraints on memory utilization, power consumption, and I/O throughput have increasingly become limiting factors to the advancement of high performance computing (HPC) and edge computing applications. IEEE‐754 floating‐point types have been the de facto standard for floating‐point number systems for decades, but the drawbacks of this numerical representation leave much to be desired. Alternative representations are gaining traction, both in HPC and machine learning environments. Posits have recently been proposed as a drop‐in replacement for the IEEE‐754 floating‐point representation. We survey the state‐of‐the‐art and state‐of‐the‐practice in the development and use of posits in edge computing and HPC. The current literature supports posits as a promising alternative to traditional floating‐point systems, both as a stand‐alone replacement and in a mixed‐precision environment. Development and standardization of the posit type is ongoing, and much research remains to explore the application of posits in different domains, how to best implement them in hardware, and where they fit with other numerical representations.
Emerging biocompatible nanoplatforms for the potential application in diagnosis and therapy of deep tumors
Authors: Guo Wenna , Chen Zengzhen , Tan Longfei , Gu Deen , Ren Xiangling , Fu Changhui , Wu Qiong , Meng Xianwei 
Published: September 2021

AbstractCancer, as one of the most attention‐grabbing medical problems, has been tried to solve with various methods. With the development of nanotechnology, diagnosis and therapy based on nanoplatforms have become new dawn for overcoming cancer problems. Biocompatible nanoplatforms integrating diagnosis and therapy technology for cancer have been extensively studied. Most of the reported works focus on the diagnosis and therapy of subcutaneous tumor. To promote clinical application, it is of great significance to develop efficient methods for deep tumors. This work reviews the latest research progress and future development prospects for the diagnosis and therapy of deep tumors based on biocompatible nanoplatforms. It mainly introduces four cancer diagnostic technologies (fluorescence imaging (FI), computed tomography (CT), magnetic resonance imaging (MRI), and photoacoustic imaging (PAI)) and four tumor treatment methods (phototherapy, ultrasound therapy, radiotherapy (RT), and microwave therapy (MWT)) based on the nanoplatforms. Several diagnostic techniques and treatment methods are systematically summarized and compared, and the advantages and limitations of different methods in tumors are discussed. At last, the application prospects and challenges of the nanoplatforms for the diagnosis and therapy of deep tumors are discussed. It is hoped that this review will provide some useful information for the research in this field.
The co‐administration effects of florfenicol and lasalocid on performance, biochemical and pathological parameters of muscle, heart, liver, kidney and sciatic nerve in broiler chickens
Authors: Gholami‐Ahangaran Majid , Karimi‐Dehkordi Maryam , Namjoo Abdolrasul , Shojaei Hasan , Ahmadi‐Dastgerdi Asiye 
Published: September 2021

AbstractThe study aimed to examine the effect of simultaneous application of florfenicol and lasalocid on the performance and vital organ function of chickens. For this, 300 chicks were divided into four groups. Group one to three received florfenicol, lasalocid and lasalocid plus florfenicol, respectively. Group four as the control group received a basic diet without lasalocid or florfenicol. Lasalocid was used from 7 to 35 days old, continuously. Florfenicol was used at 21 days old for 5 days. The growth indices were measured at the end of each week. The chickens were euthanized at the ages of 28 and 35 days old after collecting blood samples with and without anticoagulants. The liver, heart, muscle, kidney and sciatic nerve were collected in formalin 10% for histopathological examination. The blood and serum samples were used to determine clinical pathologic and hematologic indices. The ratio of internal organs to body weight and ratio of the right ventricle to the total ventricles (RV/TV) of the heart was measured. Results showed, the use of lasalocid decreased feed conversion rate and triglyceride, and increased total protein. Simultaneous administration of lasalocid and florfenicol affected histopathology of the liver and heart and significantly increased creatine phosphokinase, uric acid and the ratio of RV/TV of heart. The eosinophil percentage in the chickens who received florfenicol plus lasalocid was significantly higher than chickens who received florfenicol alone (p < 0.05). In conclusion, it seems that simultaneous administration of the florfenicol and lasalocid induces side‐effects especially on cardiac function and it is not recommended.
New estimation method of wind power density with three‐parameter Weibull distribution: A case on Central Inner Mongolia suburbs
Authors: Wang Wenxin , Chen Kexin , Bai Yang , Chen Yu , Wang Jianwen 
Published: September 2021

AbstractSuburbs have the potential for future wind energy development because of their open terrain, good wind conditions, closeness to the city, wind power that can be absorbed in place, and other advantages. Therefore, accurately evaluating the wind energy resources in the suburbs is particularly important. The three‐parameter Weibull distribution can accurately describe the wind speed in the suburbs, but research on the estimation of wind power density (WPD) with it is limited. On the basis of the mathematical models of wind speed probability distribution as Rayleigh, two‐parameter Weibull, and three‐parameter Weibull, a new WPD estimation formula with three‐parameter Weibull distribution is derived using the partial integration method and by introducing incomplete gamma function to solve the transcendental integration. A field experiment platform is built, and the accuracy of the formula is verified by the measured data. The analysis of the measured data collected in recent 3 years in the suburbs of Hohhot, Inner Mongolia, concludes that the statistical characteristics of the measured wind speed and the distribution of wind energy resources are more conducive to capture the scattered and changing wind energy in the suburbs by taking the month as the time scale. Moreover, the three‐parameter Weibull distribution estimated by the least square method can be used as the local wind speed model. The new method of WPD estimation can also reduce the calculation error by approximately 21.06%. This study provides an important reference for the subsequent analysis of wind power fluctuation characteristics and wind energy development planning.
Regression with linked datasets subject to linkage error
Authors: Wang Zhenbang , Ben‐David Emanuel , Diao Guoqing , Slawski Martin 
Published: September 2021

AbstractData are often collected from multiple heterogeneous sources and are combined subsequently. In combing data, record linkage is an essential task for linking records in datasets that refer to the same entity. Record linkage is generally not error‐free; there is a possibility that records belonging to different entities are linked or that records belonging to the same entity are missed. It is not advisable to simply ignore such errors because they can lead to data contamination and introduce bias in sample selection or estimation, which, in return, can lead to misleading statistical results and conclusions. For a long while, this problem was not properly recognized, but in recent years a growing number of researchers have developed methodology for dealing with linkage errors in regression analysis with linked datasets. The main goal of this overview is to give an account of those developments, with an emphasis on recent approaches and their connection to the so‐called “Broken Sample” problem. We also provide a short empirical study that illustrates the efficacy of corrective methods in different scenarios.This article is categorized under:Statistical Models > Model SelectionStatistical and Graphical Methods of Data Analysis > Robust MethodsStatistical and Graphical Methods of Data Analysis > Multivariate Analysis
Introduction to the Balkan Homicide Study
Authors: Getoš Kalac Anna-Maria 
Published: September 2021

AbstractThe Balkan Homicide Study (BHS) fills a considerable gap in current European homicide research. Its findings shed first light on the phenomenology of violence in this region of Europe. The BHS provides original empirical data from 2073 prosecution and court case files in six countries: Croatia, Hungary, Kosovo, North Macedonia, Romania, and Slovenia. By analyzing data on 2416 offenders and 2379 victims, the book at hand takes a close look at situational, criminogenic, victimogenic, and procedural characteristics of (lethal) violence in the Balkans. It thus investigates the highly heterogeneous types of different (potentially) deadly situations, thereby focusing on what might make them become deadly and what could be possible protective traits on the side of victims. Such an investigation of pathways into lethal violence becomes possible only if lethal violence (completed homicides) is studied together with non-lethal violence (attempted homicides). This approach however considerably broadens the subject and scope of homicide research, which commonly deals primarily with lethal violence. This chapter provides a brief overview of the pros and cons of such an approach and briefly sketches the study’s background. It also discusses the relevance of the criminal justice’s power to define violence, introduces the Balkan-violence-paradox, and presents the study’s conceptual, as well as terminological framework.
Violence in the Balkans: Regional Commons and Country Specifics
Authors: Getoš Kalac Anna-Maria 
Published: September 2021

AbstractThis chapter presents first findings from the BHS by providing data on main incident, offender, victim, and procedural characteristics of (lethal) violence in six countries of Southeastern Europe and the Balkans: Croatia, Hungary, Kosovo, North Macedonia, Romania, and Slovenia. The discussion will concentrate on regional commons, as well as country specifics with a particular focus on comparison between completed and attempted homicides. In terms of the type of violence, only the most relevant ones will be analyzed, whereby this relates to both the most prevalent and most interesting for the regional context. Thus, certain methodological aspects, like those related to missing data and the merging of datasets with different counting units, will be presented. Bearing in mind the overall scope of the BHS with more than 200 different variables, this chapter clearly presents but a fraction of all findings. Nevertheless, it is a solid starting point for future topic-wise more focused in-depth analyses, and will hopefully deliver food for thought on new lines of (lethal) violence and homicide research.
Multitask Recalibrated Aggregation Network for Medical Code Prediction
Authors: Sun Wei , Ji Shaoxiong , Cambria Erik , Marttinen Pekka 
Published: September 2021

AbstractMedical coding translates professionally written medical reports into standardized codes, which is an essential part of medical information systems and health insurance reimbursement. Manual coding by trained human coders is time-consuming and error-prone. Thus, automated coding algorithms have been developed, building especially on the recent advances in machine learning and deep neural networks. To solve the challenges of encoding lengthy and noisy clinical documents and capturing code associations, we propose a multitask recalibrated aggregation network. In particular, multitask learning shares information across different coding schemes and captures the dependencies between different medical codes. Feature recalibration and aggregation in shared modules enhance representation learning for lengthy notes. Experiments with a real-world MIMIC-III dataset show significantly improved predictive performance.