bluuebunny/crossref_metadata_2025 huggingface dataset:
Size-tunable bismuth quantum dots for self-powered photodetectors under ambient conditions
Authors: Zhu Jun , Chen Hongyan , Zi You , Wang Mengke , Huang Weichun
Published: October 2022

Although black phosphorus analogue, bismuthene, has been extensively investigated in recent years, yet the investigation into the photoelectronic devices is still in its infancy. In this contribution, uniform zero-dimensional (0D) bismuth (Bi) quantum dots (QDs) with different sizes were successfully synthesized by a simple solvothermal method. The as-synthesized 0D Bi QDs serve as working electrode materials by a direct deposition for photoelectrochemical (PEC)-type photodetection. The PEC results demonstrate that the as-fabricated 0D Bi QD-based electrode not only possess suitable self-powered broadband photoresponse, but also displays excellent photodetection performance. Under simulated light, the photocurrent density and photoresponsivity of the as-fabricated 0D Bi QD-based electrode can reach 2690 nA cm−2, and 22.0 μA W−1, respectively. In addition, the as-prepared Bi QDs with the average diameter of 17 nm exhibit the best PEC photoresponse behavior in the studied size range of Bi QDs, mainly ascribed to the synergistic effect of suitable band gap and accessible active sites. It is anticipated that the uniform Bi QDs can be served as building blocks for a variety of photoelectronic devices, further expanding the application prospects of bismuthene, and can provide in-depth acknowledge on the performance optimization of monoelement Bi-based optical devices.
Fisher forecasts for primordial non-Gaussianity from persistent homology
Authors: Biagetti Matteo , Calles Juan , Castiblanco Lina , Cole Alex , Noreña Jorge
Published: October 2022

We study the information content of summary statistics built from the multi-scale topology
of large-scale structures on primordial non-Gaussianity of the local and equilateral type. We use
halo catalogs generated from numerical N-body simulations of the Universe on large scales as a
proxy for observed galaxies. Besides calculating the Fisher matrix for halos in real space, we
also check more realistic scenarios in redshift space. Without needing to take a distant observer
approximation, we place the observer on a corner of the box. We also add redshift errors
mimicking spectroscopic and photometric samples. We perform several tests to assess the
reliability of our Fisher matrix, including the Gaussianity of our summary statistics and
convergence. We find that the marginalized 1-σ uncertainties in redshift space are
Δf
NL
loc ∼ 16 and Δf
NL
equi ∼ 41 on a survey volume of 1 (Gpc/h)3. These
constraints are weakly affected by redshift errors. We close by speculating as to how this
approach can be made robust against small-scale uncertainties by exploiting (non)locality.
Concealing Dirac neutrinos from cosmic microwave background
Authors: Biswas Anirban , Ghosh Dilip Kumar , Nanda Dibyendu
Published: October 2022

The existence of prolonged radiation domination prior to
the Big Bang Nucleosynthesis (BBN), starting just after the inflationary
epoch, is not yet established unanimously. If instead, the universe undergoes
a non-standard cosmological phase, it will alter the Hubble expansion rate
significantly and may also generate substantial entropy through non-adiabatic
evolution. This leads to a thumping impact on the properties of relic species
decoupled from the thermal bath before the revival of the standard radiation
domination in the vicinity of the BBN. In this work, considering the Dirac nature
of neutrinos, we have studied decoupling of ultra-relativistic right-handed
neutrinos (νR
s) in presence of two possible non-standard cosmological phases.
While in both cases we have modified Hubble parameters causing faster expansions
in the early universe, one of the situations predicts a non-adiabatic evolution
and thereby a slower redshift of the photon temperature due to the expansion.
Considering the most general form of the collision term with
Fermi-Dirac distribution and Pauli blocking factors, we have solved
the Boltzmann equation numerically to obtain ΔNeff for the
three right-handed neutrinos. We have found that for a large portion
of parameter space, the combined effect of early decoupling of νR
 
as well as the slower redshift of photon bath can easily hide the
signature of right-handed neutrinos, in spite of precise measurement
of ΔNeff, at the next generation CMB experiments
like CMB-S4, SPT-3G etc. This however will not be applicable for the scenarios
with only fast expansion.
Equation of states in the curved spacetime of slowly rotating degenerate stars
Authors: Hossain Golam Mortuza , Mandal Susobhan
Published: October 2022

We compute the equation of state for an ensemble of degenerate fermions by
using the curved spacetime of a slowly rotating axially symmetric star. We show
that the equation of state computed in such curved spacetime depends on the
gravitational time dilation as well as on the dragging of inertial frames,
unlike an equation of state computed in a globally flat spacetime. The effect
of gravitational time dilation leads to a significant enhancement of the
maximum mass limit of a degenerate neutron star. However, such an enhancement
due to the frame-dragging effect is extremely small. Nevertheless, in general
relativity the frame-dragging effect is crucial for computing angular momentum
of the star which is also shown to be enhanced significantly due to the usage of
curved spacetime in computing the equation of state.
Terahertz radiation generation in doped semiconductor interacting with femtosecond pulse in constant magnetic field
Authors: Grishkov V E , Uryupin S A
Published: October 2022

The generation of terahertz (THz) radiation in a doped semiconductor with a sufficiently large bandgap interacting with a femtosecond pulse of IR range has been investigated. Generation occurs due to the simultaneous effect on the conduction electrons of a constant magnetic field and time-dependent ponderomotive force. The spectral composition, total energy and shape of the THz radiation pulse are found.
Detection of laser-plasma experiment radiation using nanoparticle coatings as fluorescent sensors
Authors: Barberio M. , Salvadori M. , Vallières S. , Skantzakis E. , Sarkissian A. , Antici P.
Published: October 2022

In this paper, we test the possibility to use luminescence
of metal (aluminum and silver) nanoparticles (NPs), synthesized
using different laser-driven ablation methods, as sensors for
radiation detection. Energetic photon and electron radiation
produced by intense plasma induces a red-shift in the luminescence
emitted by the NPs. Observing the phenomenon over long time periods
(hours), we see an oscillating behavior of the luminescence signal,
which can be explained in terms of de-trapping of electrons caused
by energetic radiations and re-trapping in the empty levels of low
energetic electrons emitted from the plasma. Observing the
luminescence shift allows detecting electromagnetic and radiation
pollution, e.g. when dispersed in an experimental chamber.
Practical X-ray beam spectrometry with cadmium telluride detector in 10–300 kVp range at Czech Metrology Institute. Part II. Unfolding
Authors: Šolc J. , Dryák P. , Rusňák J. , Sochor V. , Vykydal Z.
Published: October 2022

The paper summarizes computational methods and software tools used at Czech Metrology Institute for unfolding of X-ray photon fluence spectra from detector spectra measured with a cadmium telluride (CdTe) spectrometer directly in the X-ray beam. Fluence spectra were determined using multi-channel unfolding software GRAVEL. Response functions were calculated by Monte Carlo (MC) method using the general-purpose code MCNP® in version 6.2 with EPRDATA14 photon cross-section tables. The detailed MC model of the CdTe spectrometer was developed and it was validated by comparison with full-energy peak detection efficiencies measured with selected radionuclide sources. The adopted methods and tools enable to fulfil requirements of the ISO 4037 standard dealing with the necessity of direct measurement of X-ray beam photon fluence spectra whose parameters do not comply with the ones listed in the standard. The instrumentation part for the X-ray beam spectrometry at CMI is described in a separate paper [1].
Urbanization and seasonality strengthens the CO2 capacity of the Red River Delta, Vietnam
Authors: Salgado Jorge , Duc` Trinh Anh , Nga Do Thu , Panizzo Virginia N , Bass Adrian M , Zheng Ying , Taylor Sarah , Roberts Lucy R , Lacey Jack H , Leng Melanie J , McGowan Suzanne
Published: October 2022

Tropical rivers are dynamic CO2 sources. Regional patterns in the partial pressure of CO2 (pCO2) and relationships with other a/biotic factors in densely populated and rapidly developing river delta regions of Southeast Asia are still poorly constrained. Over one year, at 21 sites across the river system in the Red River Delta (RRD), Vietnam, we calculated pCO2 levels from temperature, pH, and total alkalinity and inter-linkages between pCO2 and phytoplankton, water chemistry and seasonality were then assessed. The smaller, more urbanized, and polluted Day River had an annual median pCO2 of 5000 ± 3300 µatm and the larger Red River of 2675 ± 2271 µatm. pCO2 was 1.6 and 3.2 times higher during the dry season in the Day and Red rivers respectively than the rainy season. Elevated pCO2 levels in the Day River during the dry season were also 2.4-fold higher than the median value (2811 ±  3577 µatm) of calculated and direct pCO2 measurements in >20 sub/tropical rivers. By further categorizing the river data into Hanoi City vs. other less urban-populated provinces, we found significantly higher nutrients, organic matter content, and riverine cyanobacteria during the dry season in the Day River across Hanoi City. Forward selection also identified riverine cyanobacteria and river discharge as the main predictors explaining pCO2 variation in the RRD. After accounting for the shared effects (14%), river discharge alone significantly explained 12% of the pCO2 variation, cyanobacteria uniquely a further 21%, while 53% of the pCO2 variance was unexplained by either. We show that the urbanization of rivers deltas could result in increased sources of riverine pCO2, water pollution, and harmful cyanobacterial blooms. Such risks could be mitigated through water management to increase water flows in problem areas during the dry season.
Exact solutions of temperature-dependent Smoluchowski equations
Authors: Osinsky A I , Brilliantov N V
Published: October 2022

We report a number of exact solutions for temperature-dependent Smoluchowski equations (TDSEs). These equations quantify the ballistic agglomeration, where the evolution of densities of agglomerates of different size is entangled with the evolution of the mean kinetic energy (partial temperatures) of such clusters. The obtained exact solutions may be used as a benchmark to assess the accuracy and computational efficiency of the numerical approaches, developed to solve the TDSEs. Moreover, they may also illustrate the possible evolution regimes in these systems. The exact solutions have been obtained for a series of model rate coefficients, and we demonstrate that there may be an infinite number of such model coefficient which allow exact analysis. We compare our exact solutions with the numerical solutions for various evolution regimes; an excellent agreement between numerical and exact results proves the accuracy of the exploited numerical method.
Fabry–Perot interference enhanced transverse magneto-optical Kerr effect in Ce:YIG nanopore array on an anodic aluminum oxide template
Authors: Zhang Weiwei , Lu Yao , An Kang
Published: October 2022

The all-dielectric magneto-optical (MO) structure has garnered considerable interest due to its enhanced MO effect and low ohmic loss compared to the magnetoplasmonic structure. In this study, the effect of Fabry–Perot (F–P) interference on the enhancement of the transverse magneto-optical Kerr effect (T-MOKE) as well as sensing performance is theoretically investigated in a dielectric MO structure composed of cerium-substituted yttrium iron garnet (Ce:YIG) nanopore array coating a nanoporous anodic aluminum oxide (AAO) film standing on an aluminum sheet referred to as the AAO/Al template. The system is particularly interesting because the MO response is significantly enhanced in the position of the F–P interference, in which the T-MOKE signal is close to a 5-fold increase compared with the reference Ce:YIG film. Additionally, the sensing performance shows that the all-dielectric nanopore-based system proposed here provides an alternative to fabricating gas and solution detectors with low ohmic loss.
Surface-engineered Ti3C2T
x
MXene enabling rapid sodium/potassium ion storage
Authors: Zhao Yingying , Dong Guangsheng , Zhang Man , Wang Dashuai , Chen Yujin , Cao Dianxue , Zhu Kai , Chen Guohua
Published: October 2022

MXene with expanding interlayer and tunable terminations emerge as promising candidates for metal ion storage. Herein, we develop a facile urea decomposition strategy to obtain ultrathin nitrogen-modified Ti3C2T
x
(N-UT-Ti3C2T
x
) with optimized terminations as anode for sodium/potassium ion storage. Experimental results have shown that NH3 molecules produced by urea pyrolysis could introduce two types of nitrogen modifications in Ti3C2, function substitution for –OH (FS) and surface absorption on –O (SA). During subsequent hydrothermal and heating processes, the nitrogen atoms in situ substitute the lattice carbon in Ti3C2 (LS). Further, the effects of these nitrogen modifications in Ti3C2 on diffusion kinetics of Na+ and K+ are investigated by first-principles calculations. The superior Na+ storage performances of the N-UT-Ti3C2T
x
anode are the main attribute of the nitrogen modification of LS in Ti3C2, while the excellent K+ storage performances come from the synergistic effects of the nitrogen modifications of FS and LS in Ti3C2. This work emphasizes the effectiveness of surface engineering of nitrogen modifications and optimized terminations for improving the electrochemical performances of Ti3C2T
x
and inspires the design of heteroatom modified MXenes for energy storage.
Changes in extreme rainfall over mainland China induced by landfalling tropical cyclones
Authors: Su Jun , Ren Guoyu , Zhang Yingxian , Yang Guowei , Xue Xiaoying , Lee Ruyuan
Published: October 2022

Landfalling tropical cyclones (LTCs) is one of the most serious meteorological disasters in China due to the provided severe wind and heavy rainfall. Tropical cyclone–induced rainfall in China has been proved to decrease in recent decades. However, how landfalling tropical cyclone–induced extreme rainfall (LTCER) has changed across China, as well as the relationship between LTCER and LTCs remains poorly understood. Accordingly, the spatiotemporal distribution characteristics and long-term changes of LTCER over mainland China during the past 60 years were investigated, by using an Objective Synoptic Analysis Technique to identify LTCER. Mid and high latitudes are exposed to a greater risk of extreme rainfall from northward-moving landfalling tropical cyclones (LTCs). Meanwhile, LTCER tends to increase from 1960 to 2019 across mainland China (characterized by a decrease from 1960 to 1989 and an increase from 1990 to 2019). The LTCER trend exhibits a large spatial difference, with an increase near and to the north of 30°N, but no significant change to the south of 30°N. Moreover, the central latitude of the LTCER zone to the north of 30°N has shifted significantly southwards, while that to the south of 30°N has shifted north. Further analysis revealed that the average latitude of the LTC intensity centers to the north/south of 30°N exhibits the same shift to that of LTCER, indicating that the shift of LTCER has mainly been imposed by the migration of LTCs.
Methods for comparing digital applications in buildings and districts
Authors: Rehmann Felix , Cudok Falk , Streblow Rita
Published: October 2022

The so-called Energiewende is a complex task with a variety of stakeholders, regulations, technical infrastructure, and proposed solutions. Buildings are an important sector for increasing resource and energy efficiency, as in Germany around 35% of end energy usage can be attributed to them. Digital applications can help reduce these emissions through more efficient planning, operating, renovation, or demolition. Depending on the task and the parties involved, the complexity of descriptions and data models can vary from simple energy efficiency labels used in the labeling process of buildings to complex individual data models used for simulation. However, these specific information systems are often non-transferable, are hard to compare in their restrictions and requirements, and hence increase the overall costs of digital solutions. A good understanding is needed to preserve economic and ecological benefits while maintaining privacy and security aspects. To compare digital applications, a variety of solutions are identified. This paper first provides an overview of the identified solutions, namely frameworks, taxonomies, and ontologies. While the identified frameworks focus more on technological aspects and are complex to use, they provide an in-depth understanding. Taxonomies can be used for a scientific (e.g., classification of methods) comparison and provide simple relationships. Ontologies provide relationships and definitions while being task-dependent. We conclude that comparing the underlying data models of digital applications is a complex task and dependent on the application and its infrastructure. However, a variety of tasks refers to the same tools and data. After discussing these approaches, we then give an overview of digital applications developed by German researchers. Last, we give an insight on how to combine these aspects in our ongoing research. To summarize, in this paper we give an overview of the complexity involved in transferring digital solutions in the building sector, provide a method used for comparing applications and describe a solution to compare infrastructure and digital tools built for it.
Rural electrification subsidy estimation: a spatial model development and case study
Authors: Maqelepo Lefu , Williams Nathan , Taneja Jay
Published: October 2022

A global push to achieve universal electricity access, paired with drastic reductions in the cost of decentralized electricity technologies, has led to significant research on how best to roll out access to rural communities in sub-Saharan Africa. Various geospatial electrification models have been developed to aid the decision-making process considering decentralized grid alternatives such as mini-grids and solar home systems. Despite these tools suggesting that in many cases, decentralized systems are a more cost-effective electricity access pathway, grid extension still predominates in practice. This is due, at least in part, to institutional structures in most countries that provide significant direct and indirect subsidies to grid extension projects, commonly through publicly-owned utilities. These sources of finance are generally not available to primarily privately operated off-grid energy service providers. However, the subsidy provided for grid extension projects is not well understood. In this paper, we employ utility grid extension costs and revenue data, and geospatial grid infrastructure data to estimate the size and distribution of subsidy implicitly provided to rural grid extension projects for 129 communities in Mombasa County, Kenya. We also estimate subsidies for hypothetical off-grid electricity systems in the same communities that would deliver equivalent services to the grid. We allocate the cost of shared medium voltage (MV) distribution infrastructure using a marginal and an average cost method for grid extension and compare these with subsidies for off-grid systems. We find that the average of average subsidy per customer across communities for grid extension is US$5,118 and US$5,330 for the two MV cost allocation methods respectively, while for the off-grid systems the corresponding average of average subsidies are US$3,380, using a real discount rate of 1.3% evaluated from a nominal discount rate of 8% and inflation rate of 6.7%. Our results show that in the communities in our case study, 40% and 37% of the communities would command less subsidy while served by minigrids over the grid, and the switch would save 50% and 54% of the total cost for average and marginal cost allocation methods respectively. We also show that by using a multi-model approach to electrification and by reallocation of implicit subsidies that have been exclusive to grid extension to other technology options utilities can cast the net wider, without an increase in budgets.
High-dimensional genomic feature selection with the ordered stereotype logit model
Authors: Seffernick Anna Eames , Mrózek Krzysztof , Nicolet Deedra , Stone Richard M , Eisfeld Ann-Kathrin , Byrd John C , Archer Kellie J
Published: October 2022

For many high-dimensional genomic and epigenomic datasets, the outcome of interest is ordinal. While these ordinal outcomes are often thought of as the observed cutpoints of some latent continuous variable, some ordinal outcomes are truly discrete and are comprised of the subjective combination of several factors. The nonlinear stereotype logistic model, which does not assume proportional odds, was developed for these ‘assessed’ ordinal variables. It has previously been extended to the frequentist high-dimensional feature selection setting, but the Bayesian framework provides some distinct advantages in terms of simultaneous uncertainty quantification and variable selection. Here, we review the stereotype model and Bayesian variable selection methods and demonstrate how to combine them to select genomic features associated with discrete ordinal outcomes. We compared the Bayesian and frequentist methods in terms of variable selection performance. We additionally applied the Bayesian stereotype method to an acute myeloid leukemia RNA-sequencing dataset to further demonstrate its variable selection abilities by identifying features associated with the European LeukemiaNet prognostic risk score.
Machine learning alternative to systems biology should not solely depend on data
Authors: Yeo Hock Chuan , Selvarajoo Kumar
Published: October 2022

In recent years, artificial intelligence (AI)/machine learning has emerged as a plausible alternative to systems biology for the elucidation of biological phenomena and in attaining specified design objective in synthetic biology. Although considered highly disruptive with numerous notable successes so far, we seek to bring attention to both the fundamental and practical pitfalls of their usage, especially in illuminating emergent behaviors from chaotic or stochastic systems in biology. Without deliberating on their suitability and the required data qualities and pre-processing approaches beforehand, the research and development community could experience similar ‘AI winters’ that had plagued other fields. Instead, we anticipate the integration or combination of the two approaches, where appropriate, moving forward.
Domestic Violence Survivors Who Became Anti-domestic Violence Volunteers: A Qualitative Study in China
Authors: Wu Lei , Huang Yunong , Gao Yiyuan , Chen Qiang , McLaren Helen
Published: October 2022

This research examined the life experiences of domestic violence survivors in China, specifically the actions taken, experiences and meanings they ascribed in becoming anti-domestic violence volunteers. Data were collected via in-depth interviews in 2020 with ten such volunteers. Theories of posttraumatic growth and theories of volunteering provided an analytical framework. The findings showed that the volunteers’ experiences during and following their escape from violence went through three stages: from shock, self-blame and acceptance to recognition of the abuser as wholly responsible for the violence, followed by connecting domestic violence experiences to gender equality, social justice and human rights. Their actions against domestic violence also went through three stages: from endurance to breaking-away, followed by becoming anti-domestic violence volunteers. Participation in anti-domestic violence volunteer work contributed to rebuilding their perceptions of the self, the family and intimate relationships and the world. It also provided them with effective ways to recover from domestic violence and to foster resilience and experience posttraumatic growth. The findings indicated that whilst domestic violence resulted in a variety of negative impacts on survivors, they had resilience that aided recovery and they achieved posttraumatic growth through participating in anti-domestic violence volunteer work.
Sex difference in trait empathy is encoded in the human anterior insula
Authors: Wu Xiao , Lu Xuejing , Zhang Huijuan , Bi Yanzhi , Gu Ruolei , Kong Yazhuo , Hu Li
Published: October 2022

Females are considered the more empathic sex. This conventional view, however, has been challenged in the past few decades with mixed findings. These heterogeneous findings could be caused by the fact that empathy is a complex and multifaceted construct. To clarify whether sex differences exist in certain dimensions of empathy and whether they are associated with specific neural bases, this study measured trait empathy using the interpersonal reactivity index (IRI) and collected brain structural and functional magnetic resonance imaging data in a large sample of healthy participants (206 males vs. 302 females). We found that females scored higher in the personal distress (PD) subscale than males, but they were comparable to males in other IRI subscales. Sex difference in PD was encoded by brain structural (e.g. gray matter volume in left anterior insula [AI]) and functional (e.g. resting-state functional connectivity between left AI and temporoparietal junction/inferior frontal gyrus) characteristics. Notably, the relationship between sex and PD was indirect-only and serially mediated by AI-associated structural and functional characteristics. Altogether, our results suggested that sex difference existed in self-oriented affective empathy (i.e. PD) and highlighted the importance of the AI, both structurally and functionally, in mediating the sex difference in trait empathy.
A Semantic Embedding Enhanced Topic Model For User-Generated Textual Content Modeling In Social Ecosystems
Authors: Zhang Peng , Liu Baoxi , Lu Tun , Gu Hansu , Ding Xianghua , Gu Ning
Published: October 2022

The development of Information and Communication Technologies (ICT) and Web 2.0 promotes the emergence of diverse social ecosystems like social Internet of Things (IoT), social media and online communities. User-generated textual content (UGTC), which consists of unstructured texts, is the most important and common type of user-generated content in social ecosystems. UGTC in social ecosystems is generated according to two types of context information—global context (topics) and local context (semantic regularities). For UGTC modeling, topic models just consider global context but ignore semantic regularities, while semantic embedding models are on the opposite. So only utilizing topic models or semantic embedding models to model UGTC suffers from some drawbacks. For this problem, we propose a semantic embedding enhanced topic model named SEE-Twitter-LDA for accurately modeling UGTC in social ecosystems. The core of SEE-Twitter-LDA is that words are generated according to mutual semantic information of topics and semantic regularities. So global context and local context are jointly considered for UGTC modeling. By utilizing 553 098 tweets sampled from Twitter and 211 233 posts sampled from Weibo, we validate SEE-Twitter-LDA’s better performance on perplexity, topic divergence and topic coherence versus existing related models.
Efficient Robustness Verification of the Deep Neural Networks for Smart IoT Devices
Authors: Zhang Zhaodi , Liu Jing , Zhang Min , Sun Haiying
Published: October 2022

In the Internet of Things, smart devices are expected to correctly capture and process data from environments, regardless of perturbation and adversarial attacks. Therefore, it is important to guarantee the robustness of their intelligent components, e.g. neural networks, to protect the system from environment perturbation and adversarial attacks. In this paper, we propose a formal verification technique for rigorously proving the robustness of neural networks. Our approach leverages a tight liner approximation technique and constraint substitution, by which we transform the robustness verification problem into an efficiently solvable linear programming problem. Unlike existing approaches, our approach can automatically generate adversarial examples when a neural network fails to verify. Besides, it is general and applicable to more complex neural network architectures such as CNN, LeNet and ResNet. We implement the approach in a prototype tool called WiNR and evaluate it on extensive benchmarks, including Fashion MNIST, CIFAR10 and GTSRB. Experimental results show that WiNR can verify neural networks that contain over 10 000 neurons on one input image in a minute with a 6.28% probability of false positive on average.
AWFC: Preventing Label Flipping Attacks Towards Federated Learning for Intelligent IoT
Authors: Lv Zhuo , Cao Hongbo , Zhang Feng , Ren Yuange , Wang Bin , Chen Cen , Li Nuannuan , Chang Hao , Wang Wei
Published: October 2022

Centralized machine learning methods require the aggregation of data collected from clients. Due to the awareness of data privacy, however, the aggregation of raw data collected by Internet of Things (IoT) devices is not feasible in many scenarios. Federated learning (FL), a kind of distributed learning framework, can be running on multiple IoT devices. It aims to resolve the issues of privacy leakage by training a model locally on the client-side, other than on the server-side that aggregates all the raw data. However, there are still threats of poisoning attacks in FL. Label flipping attacks, typical data poisoning attacks in FL, aim to poison the global model by sending model updates trained by the data with mismatched labels. The central parameter aggregation server is hard to detect the label flipping attacks due to its inaccessibility to the client in a typical FL system. In this work, we are motivated to prevent label flipping poisoning attacks by observing the changes in model parameters that were trained by different single labels. We propose a novel detection method called average weight of each class in its associated fully connected layer. In this method, we detect label flipping attacks by identifying the differences of classes in the data based on the weight assignments in a fully connected layer of the neural network model and use the statistical algorithm to recognize the malicious clients. We conduct extensive experiments on benchmark data like Fashion-MNIST and Intrusion Detection Evaluation Dataset (CIC-IDS2017). Comprehensive experimental results demonstrated that our method has the detection accuracy over 90% for the identification of the attackers flipping labels.
A Consensus Diagnosis Utilizing Surface KI-67 Expression as an Ancillary Marker in Low-Grade Dysplasia Helps Identify Patients at High Risk of Progression to High-Grade Dysplasia and Esophageal Adenocarcinoma
Authors: Lee Christina , Hayat Umar , Song Kevin , Gravely Amy A , Mesa Hector , Peltola Justin , Iwamoto Carlos , Manivel Carlos , Bilal Mohammad , Shaheen Nicholas , Shaukat Aasma , Hanson Brian J
Published: October 2022

Esophageal adenocarcinoma (EAC) develops in a step-wise manner, from low-grade dysplasia (LGD) to high-grade dysplasia (HGD), and ultimately to invasive EAC. However, there remains diagnostic uncertainty about LGD and its risk of progression to HGD/EAC. The aim is to investigate the role of Ki-67, immune-histochemical marker of proliferation, surface expression in patients with confirmed LGD, and risk stratify progression to HGD/EAC. A retrospective cohort study was conducted. Patients with confirmed LGD and indefinite for dysplasia (IND), with a mean follow-up of ≥1 year, were included. Pathology specimens were stained for Ki-67 and analyzed for evidence of surface expression. Our results reveal that 29% of patients with confirmed LGD who stained positive with Ki-67 progressed to HGD/EAC as opposed to none (0%) of the patients who stained negative, a statistically significant result (P = 0.003). Similarly, specimens from patients with IND were stained and analyzed revealing a nonsignificant trend toward a higher rate of progression for Ki-67 positive cases versus Ki-67 negative, 30% versus 21%, respectively. Ki-67 expression by itself can identify patients with LGD at a high risk of progression.
Safety of same-day discharge after peroral endoscopic myotomy
Authors: Sarkis Yara , Al-Haddad Mohammad A , Siwiec Robert , Kessler William R , Wo John M , Stainko Sarah , Perkins Anthony , DeWitt John M
Published: October 2022

There are limited data on the safety of same-day discharge (SDD) after peroral endoscopic myotomy (POEM). The aim of our study is to assess the frequency and relationship to POEM for emergency department (ED) visits and hospitalizations after SDD in these patients. We retrospectively identified consecutive patients between November 2019 and August 2021 who underwent POEM with SDD and at least 6 months follow-up. Criteria for SDD includes: (1) no serious procedure-related adverse event; (2) post-POEM esophagram without leak; (3) stable vital signs; (4) ability to take liquids orally; (5) pain controlled without IV analgesia; (6) adequate social support; (7) American Society of Anesthesiologists (ASA) class I–III. A causative relationship between POEM and ED visits and hospitalizations was assigned by consensus. Out of 185 POEMs performed, 78 (41.7%, 42M, mean 51±16 years) had SDD. Within 30 days of POEM, 8 ED visits occurred in 7/78 (9%) patients and 2 (25%) were considered related to POEM; hospitalization was required in 3 (38%). After 30 days, 11 ED visits occurred in 10/78 (12.8%) patients and 1 (9%) was considered related to POEM; hospitalization was required in 5 (45%). In this study of consecutive SDD patients after POEM, 3/19 (16%) ED visits and 2/8 (25%) hospitalizations within 6 months were considered related to the procedure. Therefore, eligible patients who follow and fulfill a strict protocol after POEM may be safely discharged the same day.
Ion transport peptide regulates energy intake, expenditure, and metabolic homeostasis inDrosophila
Authors: Gáliková Martina , Klepsatel Peter
Published: October 2022

In mammals, energy homeostasis is regulated by the antagonistic action of hormones insulin and glucagon. However, in contrast to the highly conserved insulin, glucagon is absent in most invertebrates. Although there are several endocrine regulators of energy expenditure and catabolism (such as the adipokinetic hormone), no single invertebrate hormone with all of the functions of glucagon has been described so far. Here, we used genetic gain- and loss-of-function experiments to show that the Drosophila gene Ion transport peptide (ITP) codes for a novel catabolic regulator that increases energy expenditure, lowers fat and glycogen reserves, and increases glucose and trehalose. Intriguingly, Ion transport peptide has additional functions reminiscent of glucagon, such as inhibition of feeding and transit of the meal throughout the digestive tract. Furthermore, Ion transport peptide interacts with the well-known signaling via the Adipokinetic hormone; Ion transport peptide promotes the pathway by stimulating Adipokinetic hormone secretion and transcription of the receptor AkhR. The genetic manipulations of Ion transport peptide on standard and Adipokinetic hormone-deficient backgrounds showed that the Adipokinetic hormone peptide mediates the hyperglycemic and hypertrehalosemic effects of Ion transport peptide, while the other metabolic functions of Ion transport peptide seem to be Adipokinetic hormone independent. In addition, Ion transport peptide is necessary for critical processes such as development, starvation-induced foraging, reproduction, and average lifespan. Altogether, our work describes a novel master regulator of fly physiology with functions closely resembling mammalian glucagon.
More Gamer, Less Girl: Gendered Boundaries, Tokenism, and the Cultural Persistence of Masculine Dominance
Authors: Drenten Jenna , Harrison Robert L , Pendarvis Nicholas J
Published: October 2022

How do exclusionary boundaries persist in consumption subcultures amid increased progress, representation, and inclusion? In video gaming, women have come to represent nearly half of the market; yet, this is a limited indicator of gender-based progress. A culture of masculine dominance persists. Extending previous research on boundary work, the authors employ a cultural perspective of tokenism to examine how gendered boundaries in consumption subcultures persist despite efforts to transform or even eradicate them. This qualitative study draws on interviews with 23 gamers who identify as women (ages 19–29 years), coupled with data from social media platforms, news media, and industry reports. Empirical findings capture the recursive process of maladaptive boundary crossing: how women’s efforts to subvert gendered boundaries at the micro level (e.g., through response enactments) get churned through the structuring tokenistic mechanics of boundary work at the meso level and result in the inadvertent cultural persistence of masculine dominance. The analysis offers a conceptual framework that explains how micro–meso level dynamics perpetuate and conceal inequity in consumption subcultures. Implications address the precarious promise of progress and the cultural legacy of tokenism in the marketplace with particular relevance to broader systems of domination.
The Bauhaus Centennial in International Publications
Authors: Aynsley Jeremy , Cleven Esther
Published: October 2022

The Bibliography highlights new works that were published to mark the Bauhaus centennial year of 2019. The listing is arranged under 10 headings that distinguish the kinds of publication by different category. In compiling the Bibliography, particular efforts were made to identify works in languages beyond English and German.
The probabilistic random forest applied to the QUBRICS survey: improving the selection of high-redshift quasars with synthetic data
Authors: Guarneri Francesco , Calderone Giorgio , Cristiani Stefano , Porru Matteo , Fontanot Fabio , Boutsia Konstantina , Cupani Guido , Grazian Andrea , D’Odorico Valentina , Murphy Michael T , Bongiorno Angela , Saccheo Ivano , Nicastro Luciano
Published: October 2022

Several recent works have focused on the search for bright, high-z quasars (QSOs) in the South. Among them, the QUasars as BRIght beacons for Cosmology in the Southern hemisphere (QUBRICS) survey has now delivered hundreds of new spectroscopically confirmed QSOs selected by means of machine learning algorithms. Building upon the results obtained by introducing the probabilistic random forest (PRF) for the QUBRICS selection, we explore in this work the feasibility of training the algorithm on synthetic data to improve the completeness in the higher redshift bins. We also compare the performances of the algorithm if colours are used as primary features instead of magnitudes. We generate synthetic data based on a composite QSO spectral energy distribution. We first train the PRF to identify QSOs among stars and galaxies, then separate high-z quasar from low-z contaminants. We apply the algorithm on an updated data set, based on SkyMapper DR3, combined with Gaia eDR3, 2MASS, and WISE magnitudes. We find that employing colours as features slightly improves the results with respect to the algorithm trained on magnitude data. Adding synthetic data to the training set provides significantly better results with respect to the PRF trained only on spectroscopically confirmed QSOs. We estimate, on a testing data set, a completeness of $\sim 86{{\ \rm per\ cent}}$ and a contamination of $\sim 36{{\ \rm per\ cent}}$. Finally, 206 PRF-selected candidates were observed: 149/206 turned out to be genuine QSOs with z > 2.5, 41 with z < 2.5, 3 galaxies and 13 stars. The result confirms the ability of the PRF to select high-z quasars in large data sets.
A panchromatic view of infrared quasars: excess star formation and radio emission in the most heavily obscured systems
Authors: Andonie Carolina , Alexander David M , Rosario David , Laloux Brivael , Georgakakis Antonis , Morabito Leah K , Villforth Carolin , Avirett-Mackenzie Mathilda , Rivera Gabriela Calistro , Del Moro Agnese , Fotopoulou Sotiria , Harrison Chris , Lapi Andrea , Petley James , Petter Grayson , Shankar Francesco
Published: October 2022

To understand the active galactic nuclei (AGNs) phenomenon and their impact on the evolution of galaxies, a complete AGN census is required; however, finding heavily obscured AGNs is observationally challenging. Here we use the deep and extensive multiwavelength data in the COSMOS field to select a complete sample of 578 infrared (IR) quasars ($L_{\rm AGN,IR}\gt 10^{45}\rm \: erg\: s^{-1}$) at z < 3, with minimal obscuration bias, using detailed UV-to-far-IR spectral energy distribution (SED) fitting. We complement our SED constraints with X-ray and radio observations to further investigate the properties of the sample. Overall, 322 of the IR quasars are detected by Chandra and have individual X-ray spectral constraints. From a combination of X-ray stacking and $L_{\rm 2-10\rm \,kev}$ – $L_{\rm 6\: \mu m}$ analyses, we show that the majority of the X-ray faint and undetected quasars are heavily obscured (many are likely Compton thick), highlighting the effectiveness of the mid-IR band to find obscured AGNs. We find that 355 (≈61 per cent) IR quasars are obscured ($N_{\rm H}\gt 10^{22}\rm \: cm^{-2}$) and identify differences in the average properties between the obscured and unobscured quasars: (1) obscured quasars have star formation rates ≈3 times higher than unobscured systems for no significant difference in stellar mass and (2) obscured quasars have stronger radio emission than unobscured systems, with a radio-loudness parameter $\approx 0.2 \rm \: dex$ higher. These results are inconsistent with a simple orientation model but in general agreement with either extreme host-galaxy obscuration towards the obscured quasars or a scenario where obscured quasars are an early phase in the evolution of quasars.
Variability of eclipse timing: the case of V471 Tauri
Authors: Kundra Emil , Hambálek Ľubomír , Vanaverbeke Siegfried , Dubovský Pavol , Logie Ludwig , Rau Steve , Dubois Franky
Published: October 2022

The post-common envelope binary V471 Tauri has been an object of interest for decades. V471 Tau shows various phenomena due to its evolutionary state and unique properties, e.g. its magnetic accretion and eclipse timing variation (ETV). Previous authors explained the ETVs by different sometimes contradictory theories. In this paper, we present and analyse the variability of the eclipse timing of this star. We observed V471 Tauri over the last 10 yr and covered the second cycle of its period variation. Based on our analysis of the presented data, we assess the possible existence of a brown dwarf in this system and derive its orbital parameters. We compare the results of our dynamical modelling to the solution predicted by Applegate-mechanism theories, which have been developed in recent studies. We found that the observed ETV cannot be explained only by the presence of additional components to the binary.
Common-envelope shaping of planetary nebulae – IV. From protoplanetary to planetary nebula
Authors: García-Segura Guillermo , Taam Ronald E , Ricker Paul M
Published: October 2022

We present 2D hydrodynamical simulations of the transition of a protoplanetary nebula (PPN) to a planetary nebula for central stars in binary systems that have undergone a common-envelope event. After 1000 yr of magnetically driven dynamics (PPN phase), a line-driven stellar wind is introduced into the computational domain and the expansion of the nebula is simulated for another 10 000 yr, including the effects of stellar photoionization. In this study we consider central stars with main sequence (final) masses of 1 (0.569) and 2.5 (0.677) M⊙, together with a 0.6-M⊙ main-sequence companion. Extremely bipolar, narrow-waisted PPNe result in bipolar planetary nebulae, while the rest of the shapes mainly evolve into elliptical planetary nebulae. The initial magnetic field’s effects on the collimated structures, such as jets, tend to disappear in most of the cases, leaving behind the remnants of those features in only a few cases. Equatorial zones fragmented mainly by photoionization (1-M⊙progenitors), result in ‘necklace’ structures made of cometary clumps aligned with the radiation field. On the other hand, fragmentation by photoionization and shocked wind (2.5-M⊙progenitors) give rise to the formation of multiple clumps in the latitudinal direction, which remain within the lobes, close to the center, which are immersed and surrounded by hot shocked gas, not necessarily aligned with the radiation field. These results reveal that the fragmentation process has a dependence on the stellar-mass progenitor. This fragmentation is made possible by the distribution of gas in the previous post-common-envelope PPN as sculpted by the action of the jets.
Testing for spectral index variations in polarized CMB foregrounds
Authors: de Belsunce Roger , Gratton Steven , Efstathiou George
Published: October 2022

We present a Bayesian parametric component separation method for polarized microwave sky maps. We solve jointly for the primary cosmic microwave background (CMB) signal and the main Galactic polarized foreground components. For the latter, we consider electron-synchrotron radiation and thermal dust emission, modelled in frequency as a power law and a modified blackbody, respectively. We account for inter-pixel correlations in the noise covariance matrices of the input maps and introduce a spatial correlation length in the prior matrices for the spectral indices β. We apply our method to low-resolution polarized Planck 2018 Low and High Frequency Instrument (LFI/HFI) data, including the SRoll2 re-processing of HFI data. We find evidence for spatial variation of the synchrotron spectral index, and no evidence for depolarization of dust. Using the HFI SRoll2 maps, and applying wide priors on the spectral indices, we find a mean polarized synchrotron spectral index over the unmasked sky of $\bar{\beta }_{\rm sync}=-2.83\pm 0.62$. For polarized thermal dust emission, we obtain $\bar{\beta }_{\rm dust}=1.43\pm 0.24$. Using our recovered CMB maps and associated uncertainties, we constrain the optical depth to reionization, τ, using a cross-spectrum-based likelihood-approximation scheme (momento) to be τ = 0.0598 ± 0.0059. We confirm our findings using a pixel-based likelihood (pixLike). In both cases, we obtain a result that is consistent with that found by subtracting spatially uniform foreground templates. While the latter method is sufficient for current polarization data from Planck, next-generation space-borne CMB experiments will need more powerful schemes such as the one presented here.