bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metaplectic operator approach to Gutzwiller’s trace formula
Authors: Lee Min-Ho 
Published: January 2023

Abstract
We derive the Gutzwiller’s trace formula by considering the time-evolution operator of the Hamiltonian which describes an N-dimensional time-dependent generalized harmonic oscillator with general force terms, where the time-evolution operator is composed of metaplectic and Weyl-Heisenberg operators. The Hamiltonian is constructed by expanding a wave packet quadratically in position and momentum operators around a reference trajectory. Using the explicit form of the metaplectic operator recently obtained in (2022, J. Korean Phys. Soc.
80, 95), we give the proof of the well known properties of the metaplectic operator, and using those properties, we derive Gutzwiller’s trace formula and investigate the Maslov index appearing in the formula.
Redshift requirements for cosmic shear with intrinsic alignment
Authors: Fischbacher Silvan , Kacprzak Tomasz , Blazek Jonathan , Refregier Alexandre 
Published: January 2023

Abstract
Intrinsic alignment (IA) modelling and photometric redshift estimation are two of the main
sources of systematic uncertainty in weak lensing surveys. We investigate the impact of redshift
errors and their interplay with different IA models. Generally, errors on the mean δz
and
on the width σz
of the redshift bins can both lead to biases in cosmological constraints.
We find that such biases can, however, only be partially resolved by marginalizing over δz

and σz
. For Stage-III surveys, δz
and σz
cannot be well constrained due
to limited statistics. The resulting biases are thus sensitive to prior volume effects. For
Stage-IV surveys, we observe that marginalizing over the redshift parameters has an impact and
reduces the bias. We derive requirements on the uncertainty of σz
and δz
for both
Stage-III and Stage-IV surveys. We assume that the redshift systematic errors on S
8 should be
less than half of the statistical errors, and the median bias should be smaller than 0.25σ.
We find that the uncertainty on δz
has to be ≲ 0.025 for the NLA IA model with a
Stage-III survey. We find no requirement threshold for σz
since the requirements are met
even for our maximum prior width of 0.3. For the TATT IA model, the uncertainty on δz
has
to be ≲ 0.02 and the uncertainty on σz
has to be ≲ 0.2. Current redshift
precision of Stage-III surveys is therefore high enough to meet these requirements. For Stage-IV
surveys, systematic effects will be more important due to the higher statistical precision. In
this case, the uncertainty on δz
has to be ≲ 0.005 and the uncertainty
on σz
should be ≲ 0.1, with no significant dependence on the IA model. This
required high precision will be a challenge for the redshift calibration of these future surveys.
Finally, we investigate whether the interplay between redshift systematics and IA modelling can
explain the S
8-tension between cosmic shear results and CMB measurements. We find that this is
unlikely to explain the current S
8-tension. The code that was used to conduct this
analysis is publicly available.[refrigerator: https://cosmo-gitlab.phys.ethz.ch/cosmo_public/refrigerator.]
ATLAS LAr calorimeter commissioning for LHC Run-3
Authors: Zang J. 
Published: January 2023

Abstract
To cope with the increase of the luminosity at Run-3 of the LHC, new trigger readout electronics have been installed on the Liquid Argon Calorimeters. More than 1500 boards of the legacy system were refurbished and re-installed, 124 new on-detector boards and 116 new back-end mezzanine cards equipped with large FPGAs were added to digitize the calorimeter trigger signals. All the monitoring and control infrastructure is being adapted and commissioned. These proceedings will present the challenges of the installation, the commissioning, and the works still to be completed toward the full operation of both the legacy and the digital trigger in the LHC Run-3.
Performance characterization and radiation tolerance evaluation of the SSA2 ASIC, the strip sensor readout ASIC of the CMS Outer Tracker at the HL-LHC
Authors: Caratelli A. , Bergamin G. , Ceresa D. , Kaplon J. , Kloukinas K. , Nedergaard C. , Nookala A. , Scarfi S. 
Published: January 2023

Abstract
This contribution presents the results of the performance characterization and radiation tolerance evaluation of the SSA2 ASIC, the short-strip readout ASIC for the CMS Outer-Tracker PS-module. The ASIC performance is characterised by different temperatures and operating conditions, at the die level as well as at the wafer level. The radiation evaluation comprises Total-Ionising-Dose (TID) tests and Single-Event-Effects (SEEs). Wafer-level testing provided a large dataset to evaluate the production yield. The presented test results are in agreement with the design simulations and are well within the application requirements for operation in the CMS outer-tracker at the HL-LHC.
10 ps timing with highly irradiated 3D trench silicon pixel sensors
Authors: Lampis A. , Borgato F. , Brundu D. , Cardini A. , Cossu G.M. , Dalla Betta G.-F. , Garau M. , La Delfa L. , Lai A. , Loi A. , Obertino M. , Simi G. , Vecchi S. 
Published: January 2023

Abstract
In this paper the results of a beam test characterization campaign of 3D trench silicon pixel sensors are presented. A time resolution in the order of 10 ps was measured both for non-irradiated and irradiated sensors up to a fluence of 2.5 × 1016 1 MeV neq cm−2. This feature and a detection efficiency close to 99% make this sensors one of the best candidates for 4D tracking detectors in High-Energy-Physics experiments.
Characterization of 3.2 Gbps readout in 65 nm CMOS technology
Authors: Jirsa J. , Gecnuk J. , Havranek M. , Janoska Z. , Jansky M. , Kafka V. , Korchak O. , Kostina A. , Lednicky D. , Marcisovska M. , Marcisovsky M. , Stanek P. , Tomasek L. , Vancura P. 
Published: January 2023

Abstract
A new class of photon-counting pixel detectors allows for capturing of an image in several photon energy bins in one shot. A decreased pixel pitch and an increased number of energy bins are needed to enhance the spatial and spectral resolution of the detector. This led to new requirements for the readout systems and their bandwidths, as more data is generated for the same detection area. Fast differential serial communication enables high-speed data rates, thus providing an ideal solution to transfer large amounts of data generated by the detector’s front-end electronics. However, its implementation provides extra challenges. This work introduces a novel high-speed serial readout designed in a 65 nm CMOS technology that will be used in the future photon-counting X-ray imaging detectors. The design of the serial transmitter is presented together with the characterization of jitter and channel performance.
Simulating future climate change impacts on snow- and ice-related driving hazards in Arctic-boreal regions
Authors: Greaves Heather E , Boelman Natalie T , Brinkman Todd J , Liston Glen E , Prugh Laura R , Reinking Adele K 
Published: January 2023

Abstract
As Arctic and boreal regions rapidly warm, the frequency and seasonal timing of hazardous driving conditions on all-season Arctic-boreal roads are likely to change. Because these roads link remote Arctic areas to the rest of the North American road system, climate change may substantially affect safety and quality of life for northern residents and commercial enterprises. To gain insight into future hazardous driving conditions, we built Random Forest models that predict the occurrence of hazardous driving conditions by linking snow, ice, and weather simulated by a spatially explicit modeling system (SnowModel) to archived road condition reports from two highly trafficked all-season northern roads: the Dalton Highway (Alaska, USA) and Dempster Highway (Yukon, Canada). We applied these models to downscaled future climate trajectories for the study period of 2006–2100. We estimated future trends in the frequency and timing of icy, wet-icy, and snowy road surfaces, blowing and drifting snow, and high winds. We found that as the climate warms, and the portion of the year when snow and ice occur becomes shorter, overall frequency of snow storms and ice- and snow-related driving hazards decreased. For example, the mean number of days per year when roads are covered in snow or ice decreased by 51 d (−21%) on the Dalton Highway between the 2006–2020 and 2081–2100 time periods. However, the intensity of storms was predicted to increase, resulting in higher mean annual storm wind speeds (Dalton +0.56 m s−1 [+17%]) and snowfall totals (Dalton +0.3 cm [+36%]). Our models also predicted increasing frequency of wet-icy driving conditions during November, December, January, and February, when daylength is short and hazardous conditions may be more difficult to perceive. Our findings may help road managers and drivers adapt their expectations and behaviors to minimize accident risk on Arctic-boreal roads in the future.
The Use of Pest Mobile Application for Optimizing the Sustainability Support of Pest Management in Oil Palm Plantation
Authors: Hendarjanti Henny , Indratno Sapto W. 
Published: January 2023

Abstract
The road map of the Indonesian palm oil industry, which is entering the industrial revolution 4.0, is by innovation and sustainable development of digitalization, referring to the application of machine automation and human-machine communication. As a significant player in the global palm oil industry, Indonesia has started to apply digital technology in the oil palm plantation industry. In this paper a digital early detection of pests and its contributions to sustainable pest control is explored. This technology will make it easier to monitor activities on the plantation on a regular basis. Real-time observation is needed to find out the problem as early as possible. This collected digital information is then statistically analyzed and linked to ecosystem services to get better decisions, especially for sustainable integrated pest control (IPM). The use of smartphone technology with an HDI implementation assessment approach and the Triple Bottom Line is the company’s responsibility to the environment (planet), social (humans), and profit.
Major gaps in the information provided to patients before implantation of cardioverter defibrillators: a prospective patient European evaluation
Authors: Januszkiewicz Łukasz , Barra Sérgio , Marijon Eloi , Providencia Rui , de Asmundis Carlo , Chun Julian K R , Farkowski Michał M , Conte Giulio , Boveda Serge 
Published: January 2023

AbstractAimsInformation provided to patients prior to implantable cardioverter-defibrillator (ICD) insertion and their participation in the decision-making process are crucial for understanding ICD function and accepting this lifelong therapy. The aim of this study is to evaluate the extent to which different aspects related to ICD and quality of life were transmitted to patients prior to ICD implantation.Methods and resultsProspective, multicenter European study with an online questionnaire initiated by the European Heart Rhythm Association. The questionnaire was filled-in directly and personally by the ICD patients who were invited to participate. A total of 1809 patients (majority in their 40s–70s, with 624 women, 34.5%) from 10 European countries participated in the study. The median time from first ICD implantation was 5 years (interquartile range 2–10). Overall, 1155 patients (71.5%) felt optimally informed at the time of device implantation, however many respondents received no information about ICD-related complications (n = 801, 49.6%), driving restrictions (n = 718, 44.5%), and possibility of end-of-life ICD deactivation (n = 408, 25.4%). Of note, women were less frequently involved in the decision-making process than men (47.3% vs. 55.9%, P = 0.003) and reported to be less often optimally informed before ICD implantation than men (61.2% vs. 76.8%, P &lt; 0.001). More women mentioned the desire to have learned more about ICD therapy and the benefit/risk balance (45.4% vs. 33.7% of men; P &lt; 0.001).ConclusionsThis patient-based evaluation provides alarming findings on the lack of information provided to patients prior ICD implantation, particularly for women.
Technology, job characteristics, and retirement of aged workers: evidence from automation and IT adoption of firms in Korea
Authors: Chung Jongwoo , Lee Chulhee 
Published: January 2023

Abstract
We investigated how the adoption of a new production technology differently affects the risk of job separation of young and old employees in South Korea by analyzing establishment-level panel data linked with administrative employment insurance records on individual workers. To address potential endogeneity associated with a firm’s technology adoption, we conducted instrumental variable estimations with a two-stage residual inclusion (2SRI) approach. The results suggest that technology (indicated by newly adopted automation and increased purchase of Information Technology equipment) positively affects the overall employment of incumbent workers. However, the employment of aged workers is less favorably affected by newly adopted technologies compared to that of younger workers. In some conditions, technology adoptions increase the retirement risk of older workers absolutely as well as relative to that of younger workers. Newly adopted automation negatively affects the employment of aged workers who are engaged in clerical and support occupations or employed in the wholesale and retail industry. Estimation results according to the reason for retirement suggest that the negative effect of technology adoption on employment may be related to both labor demand and supply.
Phylogenetic analysis, computer modeling and catalytic prediction of an Amazonian soil β-glucosidase against a soybean saponin
Authors: Hernandez Andrea I , dos Santos Azevedo Raíza , Werhli Adriano V , dos Santos Machado Karina , Nornberg Bruna F , F Marins Luis 
Published: January 2023

Abstract Saponins are amphipathic glycosides with detergent properties present in vegetables. These compounds, when ingested, can cause difficulties in absorbing nutrients from food and even induce inflammatory processes in the intestine. There is already some evidence that saponins can be degraded by β-glucosidases of the GH3 family. In the present study, we evaluated, through computational tools, the possibility of a β-glucosidase (AMBGL17) obtained from a metagenomic analysis of the Amazonian soil, to catalytically interact with a saponin present in soybean. For this, the amino acid sequence of AMBGL17 was used in a phylogenetic analysis to estimate its origin and to determine its three-dimensional structure. The 3D structure of the enzyme was used in a molecular docking analysis to evaluate its interaction with soy saponin as a ligand. The results of the phylogenetic analysis showed that AMBGL17 comes from a microorganism of the phylum Chloroflexi, probably related to species of the order Aggregatinales. Molecular docking showed that soybean saponin can interact with the catalytic site of AMBGL17, with the amino acid GLY345 being important in this catalytic interaction, especially with a β-1,2 glycosidic bond present in the carbohydrate portion of saponin. In conclusion, AMBGL17 is an enzyme with interesting biotechnological potential in terms of mitigating the anti-nutritional and pro-inflammatory effects of saponins present in vegetables used for human and animal food.
Distance-based Decision-making in Oviposition byTribolium castaneumHerbst (Coleoptera: Tenebrionidae) on Low- and No-gluten Flours
Authors: Gerken Alison R , Dryer Danielle , Campbell James F 
Published: January 2023

AbstractThe increasing popularity of low- and no-gluten flours as wheat flour alternatives has driven the need to understand risks of insect pest infestation in these products. Previous research using no-choice bioassays found that the red flour beetle, Tribolium castaneum Herbst can oviposit and develop on a range of alternative flours; here we test T. castaneum preference by assessing attraction in a wind tunnel assay and oviposition preference in both small- and large-scale choice assays between alternative and wheat flour. Some flours such as buckwheat, teff, millet, rice, and rye elicit similar responses as wheat flour for both attraction and oviposition. Other flours such as cassava and oat were not preferred for either oviposition or attraction behaviors. Flours like sorghum and amaranth, had mixed preferences for oviposition, with decreased oviposition in the small arena but not the large arena. Comparisons to published developmental success rates of T. castnaeum on these dietsindicate that females can choose diets on which they have high developmental success, such as buckwheat or teff, and avoid flours like cassava where developmental success is low. However, mismatch of oviposition preference and developmental success also occurs, in flours such as rice and amaranth. These results suggest the red flour beetle has limited ability to make adaptive food selections for egg laying. Further analysis of the chemical and physical properties associated with preferred and nonpreferred flours can provide information on cues associated with egg laying as well as how these cues could be exploited in pest management programs.
Impacts of Bioassay Type on Insecticide Resistance Assessment in the German Cockroach (Blattodea: Ectobiidae)
Authors: Gits Madison P , Gondhalekar Ameya D , Scharf Michael E 
Published: January 2023

AbstractThe German cockroach, Blattella germanica (L.), is one of the most critical urban pests globally due to the health risks it imposes on people, such as asthma. Insecticides are known to manage large cockroach population sizes, but the rapid rate at which they develop resistance is a continuing problem. Dealing with insecticide resistance can be expensive and time-consuming for both the consumer and the pest management professional (PMP) applying the treatment. Each cockroach population is unique because different strains have different insecticide susceptibilities, so resistance profiles must be considered. This study addressed the above issue in a controlled laboratory setting. Cockroach strains from Indianapolis, Indiana, Danville, Illinois, and Baltimore, Maryland, USA were used. Four insecticide active ingredients (AIs) most used by consumers and PMPs were selected for testing in vial bioassays to establish resistance profiles. Next, no-choice and choice feeding assays with four currently registered bait products were performed to assess the impacts of competing food and circadian rhythms on bait resistance levels. The results indicate that emamectin benzoate (Optigard) was the most effective AI in causing the highest mortality in all strains in vial and no-choice bioassays; whereas, the other AIs and products were more impacted by resistance. The results acquired from these studies can help develop rapid tests for use by PMPs based on the no-choice feeding assay while also adding more information supporting current resistance and cross-resistance evolution theories.
Preanalytic variable effects on segmentation and quantification machine learning algorithms for amyloid-β analyses on digitized human brain slides
Authors: Oliveira Luca Cerny , Lai Zhengfeng , Harvey Danielle , Nzenkue Kevin , Jin Lee-Way , Decarli Charles , Chuah Chen-Nee , Dugger Brittany N 
Published: January 2023

Abstract
Computational machine learning (ML)-based frameworks could be advantageous for scalable analyses in neuropathology. A recent deep learning (DL) framework has shown promise in automating the processes of visualizing and quantifying different types of amyloid-β deposits as well as segmenting white matter (WM) from gray matter (GM) on digitized immunohistochemically stained slides. However, this framework has only been trained and evaluated on amyloid-β-stained slides with minimal changes in preanalytic variables. In this study, we evaluated select preanalytical variables including magnification, compression rate, and storage format using three digital slides scanners (Zeiss Axioscan Z1, Leica Aperio AT2, and Leica Aperio GT 450), on over 60 whole slide images, in a cohort of 14 cases having a spectrum of amyloid-β deposits. We conducted statistical comparisons of preanalytic variables with repeated measures analysis of variance evaluating the outputs of two DL frameworks for segmentation and object classification tasks. For both WM/GM segmentation and amyloid-β plaque classification tasks, there were statistical differences with respect to scanner types (p &lt; 0.05) and magnifications (p &lt; 0.05). Although small numbers of cases were analyzed, this pilot study highlights the significance of preanalytic variables that may alter the performance of ML algorithms.
Multivariate claim count regression model with varying dispersion and dependence parameters
Authors: Jeong Himchan , Tzougas George , Fung Tsz Chai 
Published: January 2023

AbstractThe aim of this paper is to present a regression model for multivariate claim frequency data with dependence structures across the claim count responses, which may be of different sign and range, and overdispersion from the unobserved heterogeneity due to systematic effects in the data. For illustrative purposes, we consider the bivariate Poisson-lognormal regression model with varying dispersion. Maximum likelihood estimation of the model parameters is achieved through a novel Monte Carlo expectation–maximization algorithm, which is shown to have a satisfactory performance when we exemplify our approach to Local Government Property Insurance Fund data from the state of Wisconsin.
Relational hyperevent models for polyadic interaction networks
Authors: Lerner Jürgen , Lomi Alessandro 
Published: January 2023

Abstract
Polyadic, or ‘multicast’ social interaction networks arise when one sender addresses multiple receivers simultaneously. Available relational event models are not well suited to the analysis of polyadic interaction networks because they specify event rates for sets of receivers as functions of dyadic covariates associated with the sender and one receiver at a time. Relational hyperevent models (RHEM) address this problem by specifying event rates as functions of hyperedge covariates associated with the sender and the entire set of receivers. We illustrate the empirical value of RHEM in a comparative reanalysis of the canonical Enron email data set.
A Bayesian decision support system for counteracting activities of terrorist groups
Authors: Shenvi Aditi , Bunnin Francis Oliver , Smith Jim Q 
Published: January 2023

AbstractWe present an integrating decision support system designed to aid security analysts’ monitoring of terrorist groups. The system comprises of (i) a dynamic network model of the level of bilateral communications between individuals and (ii) dynamic graphical models of those individual’s latent threat states. These component models are combined in a statistically coherent manner to provide measures of the imminence of an attack by the terrorist group. Domain knowledge provides the structures of the models, values of parameters and prior distributions over latent variables. Inference of the values is performed using time-series of observed data and the statistical dependencies assumed between said data and model variables. The work draws on social network and graphical models used in sociological, military, and medical fields.