bluuebunny/crossref_metadata_2025 huggingface dataset:
Large Eddy Simulation Based Computational Fluid Dynamics Investigation of the Ignition Process in Lean Spray Burner
Authors: Andreini A. , Amerighi M. , Palanti L. , Facchini B.
Published: February 2022

During the last decades, several new technologies were investigated in order to reduce the pollutant emissions and increase the overall engine efficiency. Unluckily, some of them including the lean direct injection spray combustion hinder the ignition performances of the combustor. Moreover, several expensive tests under very challenging operating conditions must be carried out to obtain the required certifications and assess the combustor behavior with respect to the ignition process. Therefore, a deeper knowledge of the phenomena involved in the flame onset is mandatory to shorten the design process and achieve the required performances from the very beginning. In the last years, computational fluid dynamics (CFD) simulations established a valid alternative to the experiments to investigate the complex phenomena involved in the ignition process. In fact, several examples are available in scientific literature about the use of simulations to predict the development of the flame starting from an initial kernel. In particular, large eddy simulation (LES) proved to be a reliable tool to uncover new mechanisms of ignition and flame stabilization in gas turbines. In this work, two reactive LES of the ignition process were attempted using ansysfluent 2019R1, with the aim of testing the thickened flame model already implemented in the solver. In fact, compared to the previous versions, a new formulation for the efficiency function based on the pioneering work of Colin was made available. Such promising tool was validated against some detailed experimental results of a lean swirled flame, known as knowledge for ignition, acoustics and instabilities (KIAI)-CORIA spray flame. At first, a non-reactive and reactive LES were carried out to validate the cold field and the stabilized flame structure respectively. Finally, two ignition simulations were performed, from initial spark deposition up to flame stabilization or kernel quenching. All the obtained results have been extensively compared against the available experimental data showing that the employed simulation setup is fairly capable of describing the phenomena involved in the rig ignition.
Robust Control of the Human Trunk Posture Using Functional Neuromuscular Stimulation: A Simulation Study
Authors: Bao Xuefeng , Audu Musa L. , Friederich Aidan R. , Triolo Ronald J.
Published: February 2022

The trunk movements of an individual paralyzed by spinal cord injury (SCI) can be restored by functional neuromuscular stimulation (FNS), which applies low-level current to the motor nerves to activate the paralyzed muscles to generate useful torques, to actuate the trunk. FNS can be modulated to vary the biotorques to drive the trunk to follow a user-defined reference motion and maintain it at a desired postural set-point. However, a stabilizing modulation policy (i.e., control law) is difficult to derive as the biomechanics of the spine and pelvis are complex and the neuromuscular dynamics are highly nonlinear, nonautonomous, and input redundant. Therefore, a control method that can stabilize it with FNS without knowing the accurate skeletal and neuromuscular dynamics is desired. To achieve this goal, we propose a control framework consisting of a robust control module that generates stabilizing torques while an artificial neural network-based mapping mechanism with an anatomy-based updating law ensures that the muscle-generated torques converge to the stabilizing values. For the robust control module, two sliding-mode robust controllers (i.e., a high compensation controller and an adaptive controller), were investigated. System stability of the proposed control method was rigorously analyzed based on the assumption that the skeletal dynamics can be approximated by Euler–Lagrange equations with bounded disturbances, which enables the generalization of the control framework. We present experiments in a simulation environment where an anatomically realistic three-dimensional musculoskeletal model of the human trunk moved in the anterior– posterior and medial–lateral directions while perturbations were applied. The satisfactory simulation results suggest the potential of this control technique for trunk tracking tasks in a typical clinical environment.
An Optimization Framework for Operational-Level Resource Composition in an Inclusive Manufacturing System
Authors: Singh Sube , Mohanty Ayush , Rai Rahul , Mahanty Biswajit , Tiwari Manoj Kumar
Published: February 2022

Manufacturing is an essential component of the economy, and globalization further influences it by the driving forces of outsourcing and distributed manufacturing with technological advances. However, the decreasing share in gross domestic product (GDP) and shrinking employment from the manufacturing sector have become concerning matters. Recently, the inclusive manufacturing paradigm has been proposed by concentrating on globally observed economic, environmental, and societal issues. This paper advances the concept of an inclusive manufacturing system (IMS) by developing an optimization-based model to enable resource composition scenarios. The developed model encapsulates an amalgamation of a realistic and complex production system, suppliers, manufacturers, assembly stations, logistics providers, and courier services. The model aims to optimize the cost and emission of manufacturing, assembly, and logistics systems while producing a product. The formulated optimization problem is discrete in nature with binary and integer decision variables and multiple complexities of nonlinear functions. Therefore, evolutionary techniques are exercised as solution approaches to handle the problem's complexity and size. A simulated case example has been designed to envision the inclusive manufacturing system by perceiving a real-life production scenario of labeling conveyor, a customized product engaged for most packaged items. The study reveals that network size influences cost and emission because of competitiveness among service providers to get the order. The result also insights that a significant share of the cost comes from production and assembling activities, whereas transportation services dominate over manufacturing-assembly activities in carbon emission.
Variational Level Set Method for Topology Optimization of Origami Fold Patterns
Authors: Ye Qian , Gu Xianfeng David , Chen Shikui
Published: February 2022

With specific fold patterns, a 2D flat origami can be converted into a complex 3D structure under an external driving force. Origami inspires the engineering design of many self-assembled and re-configurable devices. This work aims to apply the level set-based topology optimization to the generative design of origami structures. The origami mechanism is simulated using thin shell models where the deformation on the surface and the deformation in the normal direction can be simplified and well captured. Moreover, the fold pattern is implicitly represented by the boundaries of the level set function. The folding topology is optimized by minimizing a new multiobjective function that balances kinematic performance with structural stiffness and geometric requirements. Besides regular straight folds, our proposed model can mimic crease patterns with curved folds. With the folding curves implicitly represented, the curvature flow is utilized to control the complexity of the folds generated. The performance of the proposed method is demonstrated by the computer generation and physical validation of two thin shell origami designs.
Overall Pressure Loss and Heat Transfer Performance of Additively Manufactured Offset Strip Fins Used in Compact Heat Exchangers
Authors: Saltzman David , Lynch Stephen
Published: February 2022

Preliminary heat exchanger design relies heavily on correlations for overall heat transfer and pressure drop performance, particularly for heat transfer augmentation features such as fins. Extensive work has been performed by the research community to develop these correlations for the numerous designs. However, with the new technology of metal additive manufacturing and the resultant surface roughness, the traditional correlations and design considerations related to performance need to be adjusted. As a result, two metal additively manufactured offset strip fin heat exchanger geometries with different fin spacing are studied for heat transfer and pressure drop performance and compared with traditional correlations. Deviations between the additively manufactured geometries and previous correlations for smooth fins are found and are further amplified as the surface roughness-to-hydraulic diameter ratio is increased. Furthermore, the surface roughness from the additive process results in a constant friction factor behavior at high Reynolds numbers, which is unlike behavior observed for conventionally manufactured fins. Considerations for both the laminar and turbulent flow regimes are needed for correct performance prediction. A final offset strip fin geometry with a change in the fin spacing every third of the way through the flow path is tested. This study found that the orientation of fin spacing, wider spaced to tightly spaced or tightly spaced to wider spaced, did not have a significant effect on pressure drop or heat transfer. However, the study found a method for predicting the performance which will become important as additive manufacturing increases the complexity of heat exchanger designs.
A Theoretical Model for Investigating the Structural Dynamics of a Rolling Tyre
Authors: Simon Tania , La Paglia Ivano , Ripamonti Francesco , Corradi Roberto , Baro Simone
Published: February 2022

The noise generated by the rolling tyre contributes significantly to the car's interior noise. This is caused by the tyre-road contact, and at low frequencies (0–500 Hz) is mostly transmitted inside the cockpit through the structure-borne transmission path. In support of the studies in this research field, an interpretative model of the tyre-wheel system accounting for the effects induced by the angular speed represents a useful tool. To this aim, we implemented an analytical model based on a flexible ring on an elastic foundation to analyze the dynamics of the tyre-wheel system, in both static and rotating configurations. We fine-tuned the parameters of the tyre based on data coming from experimental modal analysis of the static tyre. Particular attention has been paid to the system's free and forced responses, commonly analyzed with the so-called cleat test. The results are discussed interpreting the behavior in different reference systems.
Refereeing as a Postathletic Career Option
Authors: Bright Vanessa , Warner Stacy , Zvosec Claire
Published: February 2022

Athletes may be especially primed to become referees; yet, we do not know what former athletes think about this career choice. To address the worldwide referee shortage, it is important to better understand athletes’ perceptions of refereeing. From a Career Contingency Model framework, it is evident athletes’ perception would influence their decision to consider refereeing. This study’s aim was to examine athletes’ perceptions of the refereeing environment (RQ1) and identify referee recruitment barriers (RQ2). Utilizing a descriptive phenomenological approach, 23 current and former athletes took part in semistructured interviews based on their lived experience as an athlete. The participants identified the officiating environment as a high-stress environment with financial instability, while time and lack of knowledge and support were identified as recruitment barriers. The results contributed to the burgeoning line of research attempting to address the global referee shortage and provide both theoretical and practical implications for sport managers.
Black hole spin–orbit misalignment in the x-ray binary MAXI J1820+070
Authors: Poutanen Juri , Veledina Alexandra , Berdyugin Andrei V. , Berdyugina Svetlana V. , Jermak Helen , Jonker Peter G. , Kajava Jari J. E. , Kosenkov Ilia A. , Kravtsov Vadim , Piirola Vilppu , Shrestha Manisha , Torres Manuel A. P. , Tsygankov Sergey S.
Published: February 2022

The observational signatures of black holes in x-ray binary systems depend on their masses, spins, accretion rate, and the misalignment angle between the black hole spin and the orbital angular momentum. We present optical polarimetric observations of the black hole x-ray binary MAXI J1820+070, from which we constrain the position angle of the binary orbital. Combining this with previous determinations of the relativistic jet orientation, which traces the black hole spin, and the inclination of the orbit, we determine a lower limit of 40° on the spin-orbit misalignment angle. The misalignment must originate from either the binary evolution or black hole formation stages. If other x-ray binaries have similarly large misalignments, these would bias measurements of black hole masses and spins from x-ray observations.
Deracemization through photochemical
E
/
Z
isomerization of enamines
Authors: Huang Mouxin , Zhang Long , Pan Tianrun , Luo Sanzhong
Published: February 2022

Catalytic deracemization of α-branched aldehydes is a direct strategy to construct enantiopure α-tertiary carbonyls, which are essential to pharmaceutical applications. Here, we report a photochemical
E
/
Z
isomerization strategy for the deracemization of α-branched aldehydes by using simple aminocatalysts and readily available photosensitizers. A variety of racemic α-branched aldehydes could be directly transformed into either enantiomer with high selectivity. Rapid photodynamic
E
/
Z
isomerization and highly stereospecific iminium/enamine tautomerization are two key factors that underlie the enantioenrichment. This study presents a distinctive photochemical
E
/
Z
isomerization strategy for externally tuning enamine catalysis.
Total synthesis of himastatin
Authors: D’Angelo Kyan A. , Schissel Carly K. , Pentelute Bradley L. , Movassaghi Mohammad
Published: February 2022

The natural product himastatin has an unusual homodimeric structure that presents a substantial synthetic challenge. We report the concise total synthesis of himastatin from readily accessible precursors, incorporating a final-stage dimerization strategy that was inspired by a detailed consideration of the compound’s biogenesis. Combining this approach with a modular synthesis enabled expedient access to more than a dozen designed derivatives of himastatin, including synthetic probes that provide insight into its antibiotic activity.
A framework for scintillation in nanophotonics
Authors: Roques-Carmes Charles , Rivera Nicholas , Ghorashi Ali , Kooi Steven E. , Yang Yi , Lin Zin , Beroz Justin , Massuda Aviram , Sloan Jamison , Romeo Nicolas , Yu Yang , Joannopoulos John D. , Kaminer Ido , Johnson Steven G. , Soljačić Marin
Published: February 2022

Bombardment of materials by high-energy particles often leads to light emission in a process known as scintillation. Scintillation has widespread applications in medical imaging, x-ray nondestructive inspection, electron microscopy, and high-energy particle detectors. Most research focuses on finding materials with brighter, faster, and more controlled scintillation. We developed a unified theory of nanophotonic scintillators that accounts for the key aspects of scintillation: energy loss by high-energy particles, and light emission by non-equilibrium electrons in nanostructured optical systems. We then devised an approach based on integrating nanophotonic structures into scintillators to enhance their emission, obtaining nearly an order-of-magnitude enhancement in both electron-induced and x-ray–induced scintillation. Our framework should enable the development of a new class of brighter, faster, and higher-resolution scintillators with tailored and optimized performance.
Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagement
Authors: McCallum Matthew , Czudnochowski Nadine , Rosen Laura E. , Zepeda Samantha K. , Bowen John E. , Walls Alexandra C. , Hauser Kevin , Joshi Anshu , Stewart Cameron , Dillen Josh R. , Powell Abigail E. , Croll Tristan I. , Nix Jay , Virgin Herbert W. , Corti Davide , Snell Gyorgy , Veesler David
Published: February 2022

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern evades antibody-mediated immunity that comes from vaccination or infection with earlier variants due to accumulation of numerous spike mutations. To understand the Omicron antigenic shift, we determined cryo–electron microscopy and x-ray crystal structures of the spike protein and the receptor-binding domain bound to the broadly neutralizing sarbecovirus monoclonal antibody (mAb) S309 (the parent mAb of sotrovimab) and to the human ACE2 receptor. We provide a blueprint for understanding the marked reduction of binding of other therapeutic mAbs that leads to dampened neutralizing activity. Remodeling of interactions between the Omicron receptor-binding domain and human ACE2 likely explains the enhanced affinity for the host receptor relative to the ancestral virus.
Supplemental Material: Groundwater seepage is a key driver of theater-headed valley formation in limestone
Authors: Micallef Aaron , al. et
Published: February 2022

Detailed description of the field data collection methods, sample analyses, and numerical modeling
Supplemental Material: Deep-sea hiatuses track the vigor of Cenozoic ocean bottom currents
Authors: Dutkiewicz Adriana , Müller Dietmar
Published: February 2022

Description of datasets, hiatus durations, and hiatus paleo–water depths, Table S1, Figures S1 and S2, and Video S1
Abdominal Kikuchi-Fujimoto lymphadenopathy: an uncommon presentation of a rare disease
Authors: Fiori Marco , Spina Paolo , Monotti Rita , Salvadé Igor
Published: February 2022

A 34-year-old man presented to our hospital with a 5-day history of progressive abdominal pain and fever. A CT scan identified extensive mesenteric lymphadenopathy. Initial diagnostic tests were inconclusive. Abdominal lymph node biopsy showed histiocytic necrotising lymphadenitis, compatible with Kikuchi-Fujimoto disease (KFD). This benign and self-limiting disease generally resolves following supportive treatment. In this case, remission occurred within 3 weeks of initial presentation. KFD is a very uncommon cause of lymphadenopathy, and selective mesenteric involvement is rare. Definitive diagnosis often requires lymph node biopsy. It is important to exclude more common and serious differential diagnoses associated with mesenteric lymphadenopathy, while maintaining a minimally invasive diagnostic approach, before progressing to nodal biopsy.
Bedtime versus morning use of antihypertensives for cardiovascular risk reduction (BedMed): protocol for a prospective, randomised, open-label, blinded end-point pragmatic trial
Authors: Garrison Scott R , Kolber Michael R , Allan G Michael , Bakal Jeffrey , Green Lee , Singer Alexander , Trueman Darryl R , McAlister Finlay A , Padwal Raj S , Hill Michael D , Manns Braden , McGrail Kimberlyn , O'Neill Braden , Greiver Michelle , Froentjes Liesbeth S , Manca Donna P , Mangin Dee , Wong Sabrina T , MacLean Cathy , Kirkwood Jessica EM , McCracken Rita , McCormack James P , Norris Colleen , Korownyk Tina
Published: February 2022

Introduction

Sleep-time blood pressure correlates more strongly with adverse cardiovascular events than does daytime blood pressure. The BedMed trial evaluates whether bedtime antihypertensive administration, as compared with conventional morning use, reduces major adverse cardiovascular events.

Methods and analysis

Design

Prospective randomised, open-label, blinded end-point trial.

Participants

Hypertensive primary care patients using blood pressure lowering medication and free from glaucoma.

Setting

Community primary care providers in 5 Canadian provinces (British Columbia, Alberta, Saskatchewan, Manitoba and Ontario) are mailing invitations to their eligible patients. Social media campaigns (Google, Facebook) are additionally running in the same provinces.

Intervention

Consenting participants are allocated via central randomisation to bedtime vs morning use of all antihypertensives.

Follow-up

(1) Telephone or email questionnaire at 1 week, 6 weeks, 6 months and every 6 months thereafter, and (2) accessing linked governmental healthcare databases tracking hospital and community medical services.

Primary outcome

Composite of all-cause death, or hospitalisation for myocardial infarction/acute-coronary syndrome, stroke or congestive heart failure.

Secondary outcomes

Each primary outcome element on its own, all-cause hospitalisation or emergency department visit, long-term care admission, non-vertebral fracture, new glaucoma diagnosis, 18-month cognitive decline from baseline (via Short Blessed Test).

Select other outcomes

Self-reported nocturia burden at 6 weeks and 6 months (no, minor or major burden), 1-year self-reported overall health score (EQ-5D-5L), self-reported falls, total cost of care (acute and community over study duration) and mean sleep-time systolic blood pressure after 6 months (via 24-hour monitor in a subset of 302 sequential participants).

Primary outcome analysis

Cox proportional hazards survival analysis.

Sample size

The trial will continue until a projected 254 primary outcome events have occurred.

Current status

Enrolment ongoing (3227 randomised to date).

Ethics and dissemination

BedMed has ethics approval from six research ethics review boards and will publish results in a peer-reviewed journal.

Trial registration number

NCT02990663.
Improving the diagnosis and prognosis of sepsis according to the sources of infection
Authors: Mendoza Deibie , Ascuntar Johana , Rosero Oriana , Jaimes Fabian
Published: February 2022

Introduction

The clinical presentation of sepsis is heterogeneous and largely depends on the primary site of infection. Currently, factors associated with sepsis outcomes do not differentiate between infection sites. The objective of this investigation was to identify variables associated with risk of in-hospital mortality or intensive care unit (ICU) admission, according to infection sites.

Methods

This was a secondary analysis of a multicentre prospective cohort of ED patients ≥18 years old from three university hospitals in Medellín, Colombia. Multivariable logistic regression models were performed to estimate the association of factors with in-hospital mortality or ICU admission according to five infection sites: urinary tract infection (UTI), community-acquired pneumonia (CAP), intra-abdominal infection, sepsis without evident source (primary) and other sites.

Results

The infection sites of the 1947 patients included were: UTI (n=586), CAP (n=585), intra-abdominal infection (n=213), primary (n=224) and other sites (n=339). In the multivariable model, the factors associated with in-hospital mortality or ICU admission varied by infection site: respiratory rate (RR), systolic blood pressure (SBP) and lactate for UTI; heart rate (HR), RR and temperature <38°C for CAP; Glasgow Coma Scale (GCS), lactate and age <65 for intra-abdominal infection; SBP, GCS, lactate and temperature <38°C for primary and RR, GCS and temperature <38°C for other.

Conclusions

Our results suggest that the diagnosis and prognosis of sepsis in emergency care should consider different clinical criteria, based on site of infection. Given the heterogeneity and interindividual variability of sepsis, a more individualised approach could help to direct treatment, monitor response and facilitate initial clinical decisions.
Insufficiency of compound immune checkpoint blockade to overcome engineered T cell exhaustion in pancreatic cancer
Authors: Stromnes Ingunn M , Hulbert Ayaka , Rollins Meagan R , Basom Ryan S , Delrow Jeffrey , Bonson Patrick , Burrack Adam L , Hingorani Sunil R , Greenberg Philip D
Published: February 2022

Background

Achieving robust responses with adoptive cell therapy for the treatment of the highly lethal pancreatic ductal adenocarcinoma (PDA) has been elusive. We previously showed that T cells engineered to express a mesothelin-specific T cell receptor (TCRMsln) accumulate in autochthonous PDA, mediate therapeutic antitumor activity, but fail to eradicate tumors in part due to acquisition of a dysfunctional exhausted T cell state.

Methods

Here, we investigated the role of immune checkpoints in mediating TCR engineered T cell dysfunction in a genetically engineered PDA mouse model. The fate of engineered T cells that were either deficient in PD-1, or transferred concurrent with antibodies blocking PD-L1 and/or additional immune checkpoints, were tracked to evaluate persistence, functionality, and antitumor activity at day 8 and day 28 post infusion. We performed RNAseq on engineered T cells isolated from tumors and compared differentially expressed genes to prototypical endogenous exhausted T cells.

Results

PD-L1 pathway blockade and/or simultaneous blockade of multiple coinhibitory receptors during adoptive cell therapy was insufficient to prevent engineered T cell dysfunction in autochthonous PDA yet resulted in subclinical activity in the lung, without enhancing anti-tumor immunity. Gene expression analysis revealed that ex vivo TCR engineered T cells markedly differed from in vivo primed endogenous effector T cells which can respond to immune checkpoint inhibitors. Early after transfer, intratumoral TCR engineered T cells acquired a similar molecular program to prototypical exhausted T cells that arise during chronic viral infection, but the molecular programs later diverged. Intratumoral engineered T cells exhibited decreased effector and cell cycle genes and were refractory to TCR signaling.

Conclusions

Abrogation of PD-1 signaling is not sufficient to overcome TCR engineered T cell dysfunction in PDA. Our study suggests that contributions by both the differentiation pathways induced during the ex vivo T cell engineering process and intratumoral suppressive mechanisms render engineered T cells dysfunctional and resistant to rescue by blockade of immune checkpoints.
Common characteristics between cyclic behaviours at different frequencies and monotonic behaviours of clay
Authors: Wu Tingyu , Tong Junhao , Sun Honglei , Yuan Zonghao , Guo Lin
Published: February 2022

The loading frequencies in cyclic tests and the rate of strain or stress in monotonic tests have a significant effect on the soil behaviour, particularly of clayey soil. This study aimed to determine the common characteristics of the behaviour of clay under cyclic loading at different frequencies and the relationship between cyclic and monotonic behaviours. Monotonic triaxial tests and cyclic triaxial tests at frequencies of 0.1 and 0.001 Hz were conducted on undrained saturated reconstituted soft clay. The results showed that the frequency of 0.001 Hz is sufficiently low to make the soil response comparable to that in monotonic tests. Second, there exists a unique “feature line” for cyclic tests in the plot of allowable stress versus strain, independent of the frequency. Third, the feature lines for the cyclic and monotonic tests are close and parallel to each other. Therefore, although the cyclic and monotonic loadings are quite different from each other, there are connections between these different loadings in terms of the relationship between the allowable stress and strain.
Off-centering of the disk in the halo potential and the kinematic lopsidedness in the dwarf irregular galaxy WLM
Authors: Khademi M. , Nasiri S.
Published: February 2022

In this work, to investigate the dynamical nature of the kinematic asymmetry in the isolated gas-rich dwarf irregular galaxy W LM in the Local Group, we consider that the dark matter halo and the disk do not have the same center of mass (i.e., the disk lies off-center in the potential of the extended dark matter halo), which is one of the possible physical explanations for the kinematic lopsidedness. To do so, we generate a lopsided halo potential by considering two dark matter mass density models, ISO and Burkert, and we add up the contribution to the rotation curve of a perturbation term [Formula: see text] in the gravitational potential, which arises from the offset between the disk and the dark matter halo. We show that such an m = 1 perturbation improves the rotation curve modeling when compared to a non-perturbed potential and the shape of the HI gas rotation curves is fitted better in the approaching side if the perturbation term in the halo potential is taken into account for this galaxy dynamics. In fact, displacing the disk center by 0.1 kpc from the halo center is sufficient to provide such an improvement in modeling the rotation curve.
Comparison of SUSY spectra generators for natural SUSY and string landscape predictions
Authors: Baer Howard , Barger Vernon , Martinez Dakotah
Published: February 2022

Models of natural supersymmetry give rise to a weak scale $$m_{weak}\sim m_{W,Z,h}\sim 100$$

m

weak

∼

m

W
,
Z
,
h

∼
100

GeV without any (implausible) finetuning of independent contributions to the weak scale. These models, which exhibit radiatively driven naturalness (RNS), are expected to arise from statistical analysis of the string landscape wherein large soft terms are favored, but subject to a not-too-large value of the derived weak scale in each pocket universe of the greater multiverse. The string landscape picture then predicts, using the Isajet SUSY spectra generator Isasugra, a statistical peak at $$m_h\sim 125$$

m
h

∼
125

GeV with sparticles generally beyond current LHC search limits. In this paper, we investigate how well these conclusions hold up using other popular spectra generators: SOFTSUSY, SPHENO and SUSPECT (SSS). We built a computer code DEW4SLHA which operates on SUSY Les Houches Accord files to calculate the associated electroweak naturalness measure $$\Delta _{EW}$$

Δ

EW

. The SSS generators tend to yield a Higgs mass peak $$\sim 125$$

∼
125

–127 GeV with a superparticle mass spectra rather similar to that generated by Isasugra. In an Appendix, we include loop corrections to $$\Delta _{EW}$$

Δ

EW

in a more standard notation.
Feature Selection and Spatial-Temporal Forecast of Oceanic Niño Index Using Deep Learning
Authors: Jonnalagadda Jahnavi , Hashemi Mahdi
Published: February 2022

El Niño-Southern Oscillation (ENSO) is a climate phenomenon caused due to irregular periodic oscillation in easterly winds and sea surface temperature (SST) over the tropical Pacific Ocean. ENSO is one of the main drivers of Earth’s inter-annual climate variability, which causes climate anomalies in the form of tropical cyclones, severe storms, heavy rainfalls and droughts. Due to the impact of ENSO on global climate, forecasting ENSO is of great importance. However, forecast accuracy of ENSO for a lead time of one year is low. ENSO events are forecasted through Oceanic Niño Index (ONI), which is the three-month running mean of SST anomalies over the Niño 3.4 region (5∘N-5∘S, 120∘W-170∘W). Features, such as SST, sea level pressure, zonal wind speed and meridional wind speed that contribute in determining ONI are mapped on spatial or geographical grids, where each spatial or geographical grid represents the values of one feature at a snapshot. Juxtaposing the spatial grids of all features creates a layered map at a snapshot. The layered spatial feature map is constructed at different snapshots, and they all are fed to the CLSTM to forecast ONI at lead times of 1, 3, 6, 9 and 12 months. This study employs backward stepwise feature selection based on generalization accuracy to find the most effective features. SST showed to be the best feature for forecasting ONI. Experiments showed that the CLSTM outperforms Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) and Standard Neural Network (SNN) in terms of coefficient of determination ([Formula: see text]), Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). More specifically, an improvement in [Formula: see text] values by 27.6%, 20.9%, 25% and 15.2% over CNN is observed for lead times of 3, 6, 9 and 12 months, respectively.
A Local Search Q-learning Based Approach for Multi-period Vehicle Redeployment
Authors: Ibri Sarah
Published: February 2022

The problem of vehicle redeployment in multi-period systems is studied in this paper. It is a sequential decision making problem that involves optimizing an objective over some planning horizon composed of multiple periods. In this work, the problem is handled with a hybrid local search and Q-learning algorithm. It integrates local search into the Dyna-Q algorithm and combines the system’s tactical and operational decision levels to find a multi-period policy for sharing vehicles between stations while optimizing the objective. Tests were carried out on synthetic and real instances, and the obtained results show how local search integration can improve the basic Dyna-Q algorithm.
A New Approach for Explicit Distributional Semantic Vector Representation Based on Dependency Distance and Bias Elimination
Authors: Pakzad Atefe , Analoui Morteza
Published: February 2022

We consider the problem of the semantic representation of words based on explicit basis word vectors. We focus on explicit semantic vectors in which each basis vector is equivalent to a unique word. In this paper, we propose a new approach to represent semantic vectors explicitly. The approach consists of three steps: First, we introduce two new factors called word similarity (WS) and the number of zeroes (NZ) for choosing informative context words. Second, we propose a dependency distance method by incorporating the syntactic relations of the words in the sentences. This means that the method uses not only semantic information but also syntactic one. Third, we propose two shifting methods based on WF and WS factors to eliminate the bias of the PPMI matrix. In this work, we use the ukWaC corpus to select context words and compute co-occurrence matrices. Then, we examine the results on MEN, RG-65, SimLex-999, and WordSim353 test sets. We report the performance in comparison with a Baseline in which, the word frequency has been used. The Baseline method uses a window to fix the influence of the neighboring words. Our approach improves the Spearman correlation coefficient for MEN, RG-65, SimLex-999, and WordSim353 datasets by 3.87%, 10.25%, 5.04%, and 5.24%, respectively. So, the experiment results show that the proposed context words selection, incorporating dependency distance, and using the WF-based shifting method significantly improve the performance.
Improved RFM Model for Customer Segmentation Using Hybrid Meta-heuristic Algorithm in Medical IoT Applications
Authors: Liu Yishu , Chen Chen
Published: February 2022

In Internet of Things (IoT) business applications, healthcare records and medical web service management have emerging technologies tremendous amount of data in daily transactions. The cloud service providers have attracted the attention of a huge number of user requests based on different Quality of Service (QoS) factors. The data gained researchers attention to predict user behavior through the production of IoT applications. Artificial Intelligence (AI)-based techniques have a great impact on analyzing and detection of web service segmentation and user behavior in selecting and allocating online services and online stores with wireless communications and smart devices. This research improves the Redundancy, Frequency, and Maintenance value (RFM) model to evaluate healthcare records using a hybrid Grouping Genetic Algorithm (GGA) and Density-based Spatial Clustering of Applications with Noise (DBSCAN) algorithms. In this hybrid method, using the GGA algorithm, the features selection is applied to find the optimal features for healthcare records of customer segmentation. After that, by applying the RFM model on the data output of the genetic algorithm, the data are clustered. Finally, by applying the DBSCAN algorithm, the most suitable case for clustering will be selected. The simulation results show that the accuracy of the genetic algorithm is 97% and the final clustering accuracy is 92%.
An Intelligent Deep Learning Enabled Marine Fish Species Detection and Classification Model
Authors: Mana Suja Cherukullapurath , Sasipraba T.
Published: February 2022

In recent times, marine fish species recognition becomes an important research area to protect the ocean environment. It is a tough and time-consuming operation to manually detect marine fish species on the ocean floor. Depending on the situation, extensive sample efforts may be required. These efforts might be harmful to the marine ecosystem. Automated classification methods are capable of properly classifying these fish on a consistent basis. An increasing number of people are becoming interested in utilizing electronic monitoring and reporting with artificial intelligence for the aim of fish identification and enhancing present techniques. It is becoming more usual to use video and pictures of fish (either underwater or on ships) in fishing operations. These techniques are operational, transportable, and non-invasive, and they provide high-quality pictures at a lower cost than traditional approaches. Automated image processing techniques such as Deep Learning (DL) and Machine Learning (ML) are now available, and they may be customized to perform efficient fish species identification and segmentation. In this aspect, this paper presents an Intelligent DL based Marine Fish Species Classification (IDL-MFSC) technique. The proposed IDL-MFSC technique involves three major processes such as pre-processing, fish detection and fish classification. Primarily, Weiner filtering-based noise removal process takes place as a pre-processing step. In addition, Mask R-CNN (Mask Region Based Convolutional Neural Networks) with Residual Network as a backbone network is used for fish detection. Moreover, Optimal Deep Kernel Extreme Learning Machine (ODKELM) based classification method is employed for determining the class labels of the marine fish species in which the parameter tuning of the DKELM model takes place using Water Wave Optimization (WWO) technique. The performance of the proposed method is tested using an openly accessible Fish4Knowledge dataset. The experimental result highlights the supremacy of the IDL-MFSC technique over the recent techniques with respect to various measures.
Analysis of alpha elastically scattered by light nuclei applying different models
Authors: Amar A.
Published: February 2022

This paper reports on4He elastic scattering by [Formula: see text]Li,9Be and [Formula: see text]B angular distributions analyzed in the optical model (OM) context using Woods–Saxon (WS) potential form and double folding (DF) with distorted-wave Born approximation (DWBA), while applying the M3Y approach to the real part and a WS shape to describe the imaginary part of the optical model potential (OMP). Cluster folding (CF) with the DWBA model has also been explored for theoretical data analysis. The coupled reaction channels (CRC) method has been applied to all nuclear systems under consideration where both inelastic scattering and the transfer with elastic scattering have been involved in the analysis of experimental data. The study highlights the overall agreement between the data under the study and the concerned theoretical approaches.
Mixed *-Jordan-type derivations on *-algebras
Authors: Ferreira Bruno Leonardo Macedo , Wei Feng
Published: February 2022

Let [Formula: see text] be an *-algebra with identity [Formula: see text] and [Formula: see text] and [Formula: see text] nontrivial symmetric idempotents in [Formula: see text]. In this paper we study the characterization of nonlinear mixed *-Jordan-type derivations. In particular, if [Formula: see text] is a factor von Neumann algebra then every unital nonlinear mixed *-Jordan-type derivations are additive *-derivations.
Multi-attribute geomorphological characterization of the Cenozoic deep-water strata in the Exmouth Plateau, Northern Carnarvon Basin: a contribution to the understanding of deep-water mixed carbonate–siliciclastic environments
Authors: Ortiz-Sanguino L. L. , Tellez-Rodriguez J. J. , Bedle H.
Published: February 2022

The stratigraphic architecture and relationships to the expression of deep-water architectural elements geomorphology are explored for Cenozoic deposits in the Exmouth Plateau Sub-basin in Northern Carnarvon Basin. We used a high-quality 3D seismic survey and an integrated seismic attribute analysis to provide a guide for seismic interpretation of the mixed carbonate–siliciclastic depositional systems focused on four aspects: morphology, lithology, strata thickness and reflector distortion. Three depositional elements are classified into several categories: mass transport deposits (MTDs), channel systems (channel–levee and braided-like) and lobes, whose deposition is closely related to eustatic changes, and can be explained in a sequence stratigraphic framework. The falling stage system tract is characterized by the initial development of MTDs deposited on the basin floor and small erosive channels on the upper slope. Lobes are deposited in lowstand system tracts while highstand system tracts are characterized by the deposition of MTDs and progradational segments. This mixed carbonate–siliciclastic example proved to be sensitive to other variables such as climate (Middle Miocene Climate Optimum) and plate tectonics (northward Australian Plate drift), which affect geomorphological aspects such as the dimensions and preservation of internal characteristics.
Blockchain and Beyond: Understanding Blockchains Through Prototypes and Public Engagement
Authors: Murray-Rust Dave , Elsden Chris , Nissen Bettina , Tallyn Ella , Pschetz Larissa , Speed Chris
Published: February 2022

This article presents an annotated portfolio of projects that seek to understand and communicate the social and societal implications of blockchains, DLTs and smart contracts. These complex technologies rely on human and technical factors to deliver cryptocurrencies, shared computation and trustless protocols but have a secondary benefit in providing a moment to re-think many aspects of society, and imagine alternative possibilities. The projects use design and HCI methods to relate blockchains to a range of topics, including global supply chains, delivery infrastructure, smart grids, volunteering and charitable giving, through engaging public, exploring ideas and speculating on possible futures. Based on an extensive annotated portfolio we draw out learning for the design of blockchain systems, broadening participation and surfacing questions around imaginaries, social implications and engagement with new technology. This paints a comprehensive picture of how HCI and design can shape understandings of the future of complex technologies.
Energy Efficient Boosting of GEMM Accelerators for DNN via Reuse
Authors: Cicek Nihat Mert , Shen Xipeng , Ozturk Ozcan
Published: February 2022

Reuse-centric convolutional neural networks (CNN) acceleration speeds up CNN inference by reusing computations for similar neuron vectors in CNN’s input layer or activation maps. This new paradigm of optimizations is, however, largely limited by the overheads in neuron vector similarity detection, an important step in reuse-centric CNN. This article presents an in-depth exploration of architectural support for reuse-centric CNN. It addresses some major limitations of the state-of-the-art design and proposes a novel hardware accelerator that improves neuron vector similarity detection and reduces the energy consumption of reuse-centric CNN inference. The accelerator is implemented to support a wide variety of neural network settings with a banked memory subsystem. Design exploration is performed through RTL simulation and synthesis on an FPGA platform. When integrated into Eyeriss, the accelerator can potentially provide improvements up to 7.75\( \times \)in performance. Furthermore, it can reduce the energy used for similarity detection up to 95.46%, and it can accelerate the convolutional layer up to 3.63\( \times \)compared to the software-based implementation running on the CPU.
Graph-Enhanced Spatial-Temporal Network for Next POI Recommendation
Authors: Wang Zhaobo , Zhu Yanmin , Zhang Qiaomei , Liu Haobing , Wang Chunyang , Liu Tong
Published: February 2022

The task of next Point-of-Interest (POI) recommendation aims at recommending a list of POIs for a user to visit at the next timestamp based on his/her previous interactions, which is valuable for both location-based service providers and users. Recent state-of-the-art studies mainly employ recurrent neural network (RNN) based methods to model user check-in behaviors according to user’s historical check-in sequences. However, most of the existing RNN-based methods merely capture geographical influences depending on physical distance or successive relation among POIs. They are insufficient to capture the high-order complex geographical influences among POI networks, which are essential for estimating user preferences. To address this limitation, we propose a novel Graph-based Spatial Dependency modeling (GSD) module, which focuses on explicitly modeling complex geographical influences by leveraging graph embedding. GSD captures two types of geographical influences, i.e., distance-based and transition-based influences from designed POI semantic graphs. Additionally, we propose a novel Graph-enhanced Spatial-Temporal network (GSTN), which incorporates user spatial and temporal dependencies for next POI recommendation. Specifically, GSTN consists of a Long Short-Term Memory (LSTM) network for user-specific temporal dependencies modeling and GSD for user spatial dependencies learning. Finally, we evaluate the proposed model using three real-world datasets. Extensive experiments demonstrate the effectiveness of GSD in capturing various geographical influences and the improvement of GSTN over state-of-the-art methods.
Synthesis of Frame Field-Aligned Multi-Laminar Structures
Authors: Stutz Florian Cyril , Olsen Tim Felle , Groen Jeroen Peter , Trung Tuan Nguyen , Aage Niels , Sigmund Ole , Solomon Justin , Bærentzen Jakob Andreas
Published: February 2022

In the field of topology optimization, the homogenization approach has been revived as an important alternative to the established, density-based methods. Homogenization can represent microstructures at length scales decoupled from the resolution of the computational grid. The optimal microstructure for a single load case is an orthogonal rank-3 laminate.

Initially, we investigate where singularities occur in orthogonal rank-3 laminates and show that the laminar parts of the structures we seek are unaffected by the singularities. Based on this observation, we propose a method for generating multi-laminar structures from frame fields that describe rank-3 laminates. Rather than establishing a parametrization of the domain, we compute stream surfaces that align with the frame fields and solve an optimization problem to find a well-spaced collection of such stream surfaces. Since our method does not rely on a parametrization, we also do not need a combing of the frame fields to generate this collection. Finally, we provide a method for synthesizing multi-laminar structures from a stream surface collection. This method produces a volumetric solid for each surface and combines these to form the output.

We demonstrate our method on several frame fields produced by the homogenization approach to topology optimization.