bluuebunny/crossref_metadata_2025 huggingface dataset:
Large Eddy Simulation Study on the Relationship Between Large-Scale Turbulence Vortices and Unsteady Cavitation Around a Hydrofoil
Authors: Okabayashi Kie , Furukawa Ayumu , Otsu Takeshi , Kajishima Takeo
Published: December 2022

We conducted a large eddy simulation (LES) of cavitating turbulent flow around a Clark-Y11.7% hydrofoil at an angle of attack of 8 deg. We focused on the improvement of the reproducibility of hydrofoil performance under cavitating conditions when considering the unsteadiness of the flow field sufficiently by LES. A homogeneous cavitation model was adopted. The subgrid-scale model for LES was the one-equation dynamic model. The unsteady phenomena such as cavity oscillation and cloud cavity shedding accompanied by the reentrant jet were simulated. Large-scale spanwise vortices were also captured, which occurred intermittently from the onset of the sheet cavity. Then, the flow inside the sheet cavity was de-accelerated and the streamlines went around the sheet cavity. Streamline curvature formed a separation bubble behind the sheet cavity accompanied by a low-pressure region. Thus, the sheet cavity length was sufficient and the reproducibility of the pressure distribution around the hydrofoil and lift coefficient were improved.
Effects of acoustic nonlinearity on communication performance in soft tissues
Authors: Tabak Gizem , Oelze Michael L. , Singer Andrew C.
Published: December 2022

Acoustic communication has been gaining traction as an alternative communication method in nontraditional media, such as underwater or through tissue. Acoustic propagation is known to be a nonlinear phenomenon; nonlinear propagation of acoustic waves in soft tissues at biomedical frequencies and intensities has been widely demonstrated. However, the effects of acoustic nonlinearity on communication performance in biological tissues have not yet been examined. In this work, nonlinear propagation of a communication signal in soft tissues is analyzed. The relationship between communication parameters (signal amplitude, bandwidth, and center frequency) and nonlinear distortion of the communication signal propagating in soft tissues with different acoustic properties is investigated. Simulated experiments revealed that, unlike linear channels, bit error rates increase as signal amplitude and bandwidth increase. Linear and decision feedback equalizers fail to address the increased error rates. When tissue properties and transmission parameters can be estimated, receivers based on maximum likelihood sequence estimation approach the performance of an ideal receiver in an ideal additive white Gaussian noise channel.
Noise profiling for speech enhancement employing machine learning models
Authors: Kąkol Krzysztof , Korvel Gražina , Kostek Bożena
Published: December 2022

This paper aims to propose a noise profiling method that can be performed in near real time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features derived from the Aurora noise dataset. This is to select the best-performing classifier in the context of noise profiling. Therefore, a comparison of all classifier outcomes is shown based on effectiveness metrics. Also, confusion matrices prepared for all tested models are presented. The second part of the experiment consists of selecting the algorithm that scored the best, i.e., Naive Bayes, resulting in an accuracy of 96.76%, and using it in a noise-type recognition model to demonstrate that it can perform in a stable way. Classification results are derived from the real-life recordings performed in momentary and averaging modes. The key contribution is discussed regarding speech intelligibility improvements in the presence of noise, where identifying the type of noise is crucial. Finally, conclusions deliver the overall findings and future work directions.
A deep learning solution to the marginal stability problems of acoustic feedback systems for hearing aids
Authors: Zheng Chengshi , Wang Meihuang , Li Xiaodong , Moore Brian C. J.
Published: December 2022

For hearing aids, it is critical to reduce the acoustic coupling between the receiver and microphone to ensure that prescribed gains are below the maximum stable gain, thus preventing acoustic feedback. Methods for doing this include fixed and adaptive feedback cancellation, phase modulation, and gain reduction. However, the behavior of hearing aids in situations where the prescribed gain is only just below the maximum stable gain, called here “marginally stable gain,” is not well understood. This paper analyzed marginally stable systems and identified three problems, including increased gain at frequencies with the smallest gain margin, short whistles caused by the limited rate of decay of the output when the input drops, and coloration effects. A deep learning framework, called deep marginal feedback cancellation (DeepMFC), was developed to suppress short whistles, and reduce coloration effects, as well as to limit excess amplification at certain frequencies. To implement DeepMFC, many receiver signals in closed-loop systems and corresponding open-loop systems were simulated, and the receiver signals of the closed-loop and open-loop systems were paired together to obtain parallel signals for training. DeepMFC achieved much better performance than existing feedback control methods using objective and subjective measures.
Data-driven local average room transfer function estimation for multi-point equalization
Authors: Tuna Cagdas , Zevering Annika , Prinn Albert G. , Götz Philipp , Walther Andreas , Habets Emanuël A. P.
Published: December 2022

Multi-point room equalization (EQ) aims to achieve a desired sound quality within a wider listening area than single-point EQ. However, multi-point EQ necessitates the measurement of multiple room impulse responses at a listener position, which may be a laborious task for an end-user. This article presents a data-driven method that estimates a spatially averaged room transfer function (RTF) from a single-point RTF in the low-frequency region. A deep neural network (DNN) is trained using only simulated RTFs and tested with both simulated and measured RTFs. It is demonstrated that the DNN learns a spatial smoothing operation: notches across the spectrum are smoothed out while the peaks of the single-point RTF are preserved. An EQ framework based on a finite impulse response filter is used to evaluate the room EQ performance. The results show that while not fully reaching the level of multi-point EQ performance, the proposed data-driven local average RTF estimation method generally brings improvement over single-point EQ.
Extracellular serine empowers epidermal proliferation and psoriasis-like symptoms
Authors: Cappello Angela , Mancini Mara , Madonna Stefania , Rinaldo Serena , Paone Alessio , Scarponi Claudia , Belardo Antonio , Zolla Lello , Zuccotti Alessandro , Panatta Emanuele , Pallotta Sabatino , Annicchiarico-Petruzzelli Margherita , Albanesi Cristina , Cutruzzolà Francesca , Wang Lu , Jia Wei , Melino Gerry , Candi Eleonora
Published: December 2022

The contribution of nutrient availability to control epidermal cell proliferation, inflammation, and hyperproliferative diseases remains unknown. Here, we studied extracellular serine and serine/glycine metabolism using human keratinocytes, human skin biopsies, and a mouse model of psoriasis-like disease. We focused on a metabolic enzyme, serine hydroxymethyltransferase (SHMT), that converts serine into glycine and tetrahydrofolate-bound one‑carbon units to support cell growth. We found that keratinocytes are both serine and glycine auxotrophs. Metabolomic profiling and hypoxanthine supplementation indicated that SHMT silencing/inhibition reduced cell growth through purine depletion, leading to nucleotide loss. In addition, topical application of an SHMT inhibitor suppressed both keratinocyte proliferation and inflammation in the imiquimod model and resulted in a decrease in psoriasis-associated gene expression. In conclusion, our study highlights SHMT2 activity and serine/glycine availability as an important metabolic hub controlling both keratinocyte proliferation and inflammatory cell expansion in psoriasis and holds promise for additional approaches to treat skin diseases.
EGFR is a master switch between immunosuppressive and immunoactive tumor microenvironment in inflammatory breast cancer
Authors: Wang Xiaoping , Semba Takashi , Manyam Ganiraju C. , Wang Jing , Shao Shan , Bertucci Francois , Finetti Pascal , Krishnamurthy Savitri , Phi Lan Thi Hanh , Pearson Troy , Van Laere Steven J. , Burks Jared K. , Cohen Evan N. , Reuben James M. , Yang Fei , Min Hu , Navin Nicholas , Trinh Van Ngu , Iwase Toshiaki , Batra Harsh , Shen Yichao , Zhang Xiang , Tripathy Debu , Ueno Naoto T.
Published: December 2022

Inflammatory breast cancer (IBC), the most aggressive breast cancer subtype, is driven by an immunosuppressive tumor microenvironment (TME). Current treatments for IBC have limited efficacy. In a clinical trial (NCT01036087), an anti-EGFR antibody combined with neoadjuvant chemotherapy produced the highest pathological complete response rate ever reported in patients with IBC having triple-negative receptor status. We determined the molecular and immunological mechanisms behind this superior clinical outcome. Using novel humanized IBC mouse models, we discovered that EGFR-targeted therapy remodels the IBC TME by increasing cytotoxic T cells and reducing immunosuppressive regulatory T cells and M2 macrophages. These changes were due to diminishing immunosuppressive chemokine expression regulated by transcription factor EGR1. We also showed that induction of an immunoactive IBC TME by an anti-EGFR antibody improved the antitumor efficacy of an anti–PD-L1 antibody. Our findings lay the foundation for clinical trials evaluating EGFR-targeted therapy combined with immune checkpoint inhibitors in patients with cancer.
Dental form and function in the early feeding diversification of dinosaurs
Authors: Ballell Antonio , Benton Michael J. , Rayfield Emily J.
Published: December 2022

Dinosaurs evolved a remarkable diversity of dietary adaptations throughout the Mesozoic, but the origins of different feeding modes are uncertain, especially the multiple origins of herbivory. Feeding habits of early dinosaurs have mostly been inferred from qualitative comparisons of dental morphology with extant analogs. Here, we use biomechanical and morphometric methods to investigate the dental morphofunctional diversity of early dinosaurs in comparison with extant squamates and crocodylians and predict their diets using machine learning classification models. Early saurischians/theropods are consistently classified as carnivores. Sauropodomorphs underwent a dietary shift from faunivory to herbivory, experimenting with diverse diets during the Triassic and Early Jurassic, and early ornithischians were likely omnivores. Obligate herbivory was a late evolutionary innovation in both clades. Carnivory is the most plausible ancestral diet of dinosaurs, but omnivory is equally likely under certain phylogenetic scenarios. This early dietary diversity was fundamental in the rise of dinosaurs to ecological dominance.
Bacterial crystalline cellulose secretion via a supramolecular BcsHD scaffold
Authors: Abidi Wiem , Decossas Marion , Torres-Sánchez Lucía , Puygrenier Lucie , Létoffé Sylvie , Ghigo Jean-Marc , Krasteva Petya V.
Published: December 2022

Cellulose, the most abundant biopolymer on Earth, is not only the predominant constituent of plants but also a key extracellular polysaccharide in the biofilms of many bacterial species. Depending on the producers, chemical modifications, and three-dimensional assemblies, bacterial cellulose (BC) can present diverse degrees of crystallinity. Highly ordered, or crystalline, cellulose presents great economical relevance due to its ever-growing number of biotechnological applications. Even if some acetic acid bacteria have long been identified as BC superproducers, the molecular mechanisms determining the secretion of crystalline versus amorphous cellulose remain largely unknown. Here, we present structural and mechanistic insights into the role of the accessory subunits BcsH (CcpAx) and BcsD (CesD) that determine crystalline BC secretion in the
Gluconacetobacter
lineage. We show that oligomeric BcsH drives the assembly of BcsD into a supramolecular cytoskeletal scaffold that likely stabilizes the cellulose-extruding synthase nanoarrays through an unexpected inside-out mechanism for secretion system assembly.
Building block properties govern granular hydrogel mechanics through contact deformations
Authors: Emiroglu Dilara Börte , Bekcic Aleksandar , Dranseike Dalia , Zhang Xinyu , Zambelli Tomaso , deMello Andrew J. , Tibbitt Mark W.
Published: December 2022

Granular hydrogels have been increasingly exploited in biomedical applications, including wound healing and cardiac repair. Despite their utility, design guidelines for engineering their macroscale properties remain limited, as we do not understand how the properties of granular hydrogels emerge from collective interactions of their microgel building blocks. In this work, we related building block features (stiffness and size) to the macroscale properties of granular hydrogels using contact mechanics. We investigated the mechanics of the microgel packings through dynamic oscillatory rheology. In addition, we modeled the system as a collection of two-body interactions and applied the Zwanzig and Mountain formula to calculate the plateau modulus and viscosity of the granular hydrogels. The calculations agreed with the dynamic mechanical measurements and described how microgel properties and contact deformations define the rheology of granular hydrogels. These results support a rational design framework for improved engineering of this fascinating class of materials.
Oxygen isotopes of anhydrous primary minerals show kinship between asteroid Ryugu and comet 81P/Wild2
Authors: Kawasaki Noriyuki , Nagashima Kazuhide , Sakamoto Naoya , Matsumoto Toru , Bajo Ken-ichi , Wada Sohei , Igami Yohei , Miyake Akira , Noguchi Takaaki , Yamamoto Daiki , Russell Sara S. , Abe Yoshinari , Aléon Jérôme , Alexander Conel M. O’D. , Amari Sachiko , Amelin Yuri , Bizzarro Martin , Bouvier Audrey , Carlson Richard W. , Chaussidon Marc , Choi Byeon-Gak , Dauphas Nicolas , Davis Andrew M. , Di Rocco Tommaso , Fujiya Wataru , Fukai Ryota , Gautam Ikshu , Haba Makiko K. , Hibiya Yuki , Hidaka Hiroshi , Homma Hisashi , Hoppe Peter , Huss Gary R. , Ichida Kiyohiro , Iizuka Tsuyoshi , Ireland Trevor R. , Ishikawa Akira , Ito Motoo , Itoh Shoichi , Kita Noriko T. , Kitajima Kouki , Kleine Thorsten , Komatani Shintaro , Krot Alexander N. , Liu Ming-Chang , Masuda Yuki , McKeegan Kevin D. , Morita Mayu , Motomura Kazuko , Moynier Frédéric , Nakai Izumi , Nguyen Ann , Nittler Larry , Onose Morihiko , Pack Andreas , Park Changkun , Piani Laurette , Qin Liping , Schönbächler Maria , Tafla Lauren , Tang Haolan , Terada Kentaro , Terada Yasuko , Usui Tomohiro , Wadhwa Meenakshi , Walker Richard J. , Yamashita Katsuyuki , Yin Qing-Zhu , Yokoyama Tetsuya , Yoneda Shigekazu , Young Edward D. , Yui Hiroharu , Zhang Ai-Cheng , Nakamura Tomoki , Naraoka Hiroshi , Okazaki Ryuji , Sakamoto Kanako , Yabuta Hikaru , Abe Masanao , Miyazaki Akiko , Nakato Aiko , Nishimura Masahiro , Okada Tatsuaki , Yada Toru , Yogata Kasumi , Nakazawa Satoru , Saiki Takanao , Tanaka Satoshi , Terui Fuyuto , Tsuda Yuichi , Watanabe Sei-ichiro , Yoshikawa Makoto , Tachibana Shogo , Yurimoto Hisayoshi
Published: December 2022

The extraterrestrial materials returned from asteroid (162173) Ryugu consist predominantly of low-temperature aqueously formed secondary minerals and are chemically and mineralogically similar to CI (Ivuna-type) carbonaceous chondrites. Here, we show that high-temperature anhydrous primary minerals in Ryugu and CI chondrites exhibit a bimodal distribution of oxygen isotopic compositions:
16
O-rich (associated with refractory inclusions) and
16
O-poor (associated with chondrules). Both the
16
O-rich and
16
O-poor minerals probably formed in the inner solar protoplanetary disk and were subsequently transported outward. The abundance ratios of the
16
O-rich to
16
O-poor minerals in Ryugu and CI chondrites are higher than in other carbonaceous chondrite groups but are similar to that of comet 81P/Wild2, suggesting that Ryugu and CI chondrites accreted in the outer Solar System closer to the accretion region of comets.
Notch-dependent cooperativity between myeloid lineages promotes Langerhans cell histiocytosis pathology
Authors: Kvedaraite Egle , Milne Paul , Khalilnezhad Ahad , Chevrier Marion , Sethi Raman , Lee Hong Kai , Hagey Daniel W. , von Bahr Greenwood Tatiana , Mouratidou Natalia , Jädersten Martin , Lee Nicole Yee Shin , Minnerup Lara , Tan Yingrou , Dutertre Charles-Antoine , Benac Nathan , Hwang You Yi , Lum Josephine , Loh Amos Hong Pheng , Jansson Jessica , Teng Karen Wei Weng , Khalilnezhad Shabnam , Xu Weili , Resteu Anastasia , Tey Hong Liang , Guan Ng Lai , Larbi Anis , Howland Shanshan Wu , Arnell Henrik , Andaloussi Samir E. L. , Braier Jorge , Rassidakis Georgios , Galluzzo Laura , Dzionek Andrzej , Henter Jan-Inge , Chen Jinmiao , Collin Matthew , Ginhoux Florent
Published: December 2022

Langerhans cell histiocytosis (LCH) is a potentially fatal neoplasm characterized by the aberrant differentiation of mononuclear phagocytes, driven by mitogen-activated protein kinase (MAPK) pathway activation. LCH cells may trigger destructive pathology yet remain in a precarious state finely balanced between apoptosis and survival, supported by a unique inflammatory milieu. The interactions that maintain this state are not well known and may offer targets for intervention. Here, we used single-cell RNA-seq and protein analysis to dissect LCH lesions, assessing LCH cell heterogeneity and comparing LCH cells with normal mononuclear phagocytes within lesions. We found LCH discriminatory signatures pointing to senescence and escape from tumor immune surveillance. We also uncovered two major lineages of LCH with DC2- and DC3/monocyte-like phenotypes and validated them in multiple pathological tissue sites by high-content imaging. Receptor-ligand analyses and lineage tracing in vitro revealed Notch-dependent cooperativity between DC2 and DC3/monocyte lineages during expression of the pathognomonic LCH program. Our results present a convergent dual origin model of LCH with MAPK pathway activation occurring before fate commitment to DC2 and DC3/monocyte lineages and Notch-dependent cooperativity between lineages driving the development of LCH cells.
RORγt-lineage APCs: The Aire apparent
Authors: Gardner James M. , Liston Adrian
Published: December 2022

Recent studies shed light on new populations and potential roles of Aire
+
and RORγt
+
antigen-presenting cells—including unique subsets with surprising properties—in immune homeostasis and host-microbe interactions.
Decline of case reports in pathology and their renewal in the digital age: an analysis of publication trends over four decades
Authors: Cima Luca , Pagliuca Francesca , Torresani Evelin , Polonia Antonio , Eloy Catarina , Dhanasekeran Venkatesh , Mannan Rifat , Gamba Torrez Silvia , Mirabassi Nicola , Cassisa Angelo , Palicelli Andrea , Barbareschi Mattia
Published: December 2022

Aims

We investigated the trend in case reports (CRs) publication in a sample of pathology journals. Furthermore, we proposed an alternative publishing route through new digital communication platforms, represented by the ‘social media case report’.

Methods

28 pathology journals were selected from SCImago database and searched in PubMed to identify the number of published CRs. Four reference decades (1981–2020) were selected. The 5-year impact factor (IF) was retrieved from the Academic Accelerator database.

Results

CRs increased during the first three decades (6752, 8698 and 11148, respectively; mean values: 355, 27.3%; 334, 26.4%; 398, 28.8%) as the number of CR-publishing journals (19, 26 and 28, respectively). In the last decade, CRs significantly decreased (9341; mean 334, 23.6%) without variation in the number of CR-publishing journals (28). Half of the journals reduced CRs (from −1.1% to −37.9%; mean decreasing percentage −14.7%), especially if active since the first decade (11/14, 79%); the other half increased CRs (from +0.5% to +34.2%; mean increasing percentage +11.8%), with 8/14 (57%) starting publishing in the first decade. The 5-year IF ranged from 0.504 to 5.722. Most of the journals with IF ≥2 (10/14, 71%) reduced the CRs number, while 71% of journals with IF <2 increased CRs publication (especially journals with IF <1, +15.1%).

Conclusions

CRs publication decreased during the last decade, especially for journals which are older or have higher IF. Social media CRs may represent a valid alternative and by using standardised templates to enter all relevant data may be organised in digital databases and/or transformed in traditional CRs.
Erosion of the ‘ethical’ doctor-patient relationship and the rise of physician burn-out
Authors: Messinger Atara , Das Sunit
Published: December 2022

This paper examines the topic of physician burn-out from a philosophical lens. We explore the question of how the rise of physician burn-out may be related to an underlying erosion of meaning in medicine, characterised by the breakdown of the intersubjective relationship between doctors and patients. We argue that while commonly cited strategies for addressing burnout—including promoting work-life integration, cultivating workplace community, and fostering resilience—are critical for enhancing physician well-being, the common thread linking these approaches is that each identifies the physician as the primary locus of intervention. We propose that physician-centric approaches alone may be insufficient in addressing burnout, as the work might also involve shifting our attention to the intersubjective space that exists between the physician and the patient. To further elucidate the connection between intersubjectivity and the creation of meaning in medicine, we call on twentieth-century philosopher Emmanuel Levinas. Applying Levinas’s philosophy to the clinical context, we discuss the phenomenon of ‘depersonalisation’ and ask whether, rather than a mere consequence of burnout, depersonalisation might be a core cause of this condition. With these points we shed light on an idea that is relatively absent from the burn-out literature: that a person-oriented approach is vital not only for patient well-being but for physician wellness as well, as a process that ‘de-personalizes’ patients might result in a simultaneous dehumanisation of physicians themselves. Drawing inspiration from Levinas, we explore how a reorientation towards the intersubjective, dialogical dimension of the doctor-patient dyad could serve as one important ingredient in healing not only the patient, but the physician as well.
Direct estimates of reef fish abundance across an artificial reef network
Authors: Powers Sean P. , Drymon J. Marcus , Hightower Crystal L. , Carleton Liese M. , Hoenig John M.
Published: December 2022

Fisheries-independent surveys are commonly used to create indices of relative abundance. If properly designed and calibrated, these surveys may also be used to estimate absolute abundance. Here, we demonstrate the efficacy of this approach by estimating the absolute abundance of red lionfish ( Pterois volitans), gray triggerfish ( Balistes capriscus), and red snapper ( Lutjanus campechanus) across an extensive network of artificial reefs using camera counts, indices of relative abundance, calibration factors, and index-removal estimators. From 2012 to 2017, per reef estimates increased for red lionfish (20×), gray triggerfish (2.1×), and red snapper (2.2×). Network-wide absolute abundances were calculated by multiplying the average per reef estimate by the estimated number of reefs in the network. All increases were consistent with predictions of stock assessment (red snapper), management actions (gray triggerfish), or invasive species colonization (red lionfish). Our methodology demonstrates how estimates of absolute abundance can be derived from fishery-independent surveys and used to evaluate the outputs of stock assessments both in direction and magnitude and quantify critical ecosystem components.
Atlantic salmon of wild and hatchery origin have different migration patterns
Authors: Nilsen Cecilie I. , Vollset Knut Wiik , Velle Gaute , Barlaup Bjørn Torgeir , Normann Eirik Straume , Stöger Elisabeth , Lennox Robert James
Published: December 2022

Hatcheries are frequently used to support or restore threatened Atlantic salmon populations. However, little is known about how rearing affects behaviour and fitness of hatchery adults that return to the river to spawn. We used acoustic telemetry to compare migration patterns exhibited by hatchery ( N = 16) and wild ( N = 12) Atlantic salmon spawners within a river system in Norway. Hatchery Atlantic salmon in this study were released as smolts and were identified by their missing adipose fin upon return to rivers after 1+ winters spent at sea. Hatchery-origin Atlantic salmon displayed aberrant reverse movement behaviour, by moving with frequent reversals between the river and the fjord, a behaviour that was not observed in any wild Atlantic salmon. No difference in survival and outmigration timing after spawning was found for the two groups. The observed effect of hatchery origin on behavior may have implications for stock assessments made to assess the progress of restoration in the river, particularly if behavioural differences impact catchability or detections of returning adult salmon. The consequences of different movement patterns are uncertain; however, movements are energetically costly and may ultimately impact the fitness of hatchery Atlantic salmon.
Drivers of Atlantic herring decline and evidence basis for fisheries closures and rebuilding plans
Authors: Calder Ryan S.D. , McDermid Jenni L. , Boudreau Stephanie A.
Published: December 2022

Atlantic herring ( Clupea harengus) are economically and ecologically significant but have been in decline in Atlantic Canada due to an uncertain combination of environmental recruitment controls, predation, and fishing (commercial fishery and poorly documented bait removals). Fisheries and Oceans Canada partially closed Atlantic mackerel ( Scomber scombrus) and herring fisheries in March 2022 amid controversy and disagreement. Here, we develop a conceptual model for natural and anthropogenic controls on herring abundance centered on the southern Gulf of St. Lawrence (sGSL) and evaluate the likely importance of each. We provide the first estimates of the magnitude of bait fishery withdrawals in the sGSL. The decline in sGSL herring is likely driven by natural predation exacerbated by fishing. Bait fishery removals were 182 tonnes in 2021, suggesting that previous estimates for removals of spring-spawning herring were ∼30% too low. Fisheries closure is consistent with a precautionary approach given uncertainties and irreversibility of stock collapse. Ecosystemic models are needed but will be difficult to develop given the incomplete understanding of prey substitutability and net effect of interacting environmental processes.
On magnetic monopole and Dirac quantization condition in the minimal length formalism
Authors: Twagirayezu Fidele J.
Published: December 2022

In this article, we study the effects of minimal length corrections on the cyclotron acceleration and radiation of a charged particle moving in a magnetic monopole field. Using the modified Hamiltonian describing the dynamics of a charged particle moving in a magnetic monopole field, we derive the modified cyclotron frequency and modified acceleration. Also, we derive the modified power for the cyclotron radiation using the modified acceleration. We find that all modified quantities are dependent on the deformation parameter α. In addition, we find that the modified electromagnetic angular momentum and magnetic charges are not quantized as an integer multiple; thus, we establish that the modified Dirac quantization condition and the usual Dirac quantization condition is just the term of zero order in α. The modified Dirac quantization condition allows fractional charges that arise from vacuum fluctuations. In the Born approximation, we derive the modified scattering cross-section and then we estimate the upper bound on the minimal length.
Gauge-invariant coefficients in perturbative quantum gravity
Authors: Bastianelli Fiorenzo , Bonezzi Roberto , Melis Marco
Published: December 2022

Heat kernel methods are useful for studying properties of quantum gravity. We recompute the first three heat kernel coefficients in perturbative quantum gravity with cosmological constant to ascertain which ones are correctly reported in the literature. They correspond to the counterterms needed to renormalize the one-loop effective action in four dimensions. They may be evaluated at arbitrary dimensions D, in which case they identify only a subset of the divergences appearing in the effective action for $$D\ge 6$$

D
≥
6

. Generically, these coefficients depend on the gauge-fixing choice adopted in quantizing the Einstein–Hilbert action. However, they become gauge-invariant once evaluated on-shell, i.e. using Einstein’s equations with cosmological constant. Thus, we identify these gauge invariant coefficients and use them as a benchmark for testing alternative approaches to perturbative quantum gravity. One of these approaches describes the graviton in first-quantization through the $${{\mathcal {N}}}=4$$

N
=
4

spinning particle, characterized by four supersymmetries on the worldline and a set of worldline gauge invariances. This description has been used for computing the gauge-invariant coefficients as well. We verify their correctness at $$D=4$$

D
=
4

, but find a mismatch at arbitrary D when comparing with the benchmark fixed previously. We interpret this result as signaling that the path integral quantization of the $${{\mathcal {N}}}=4$$

N
=
4

spinning particle should be amended. We perform this task by fixing the correct counterterm that must be used in the worldline path integral quantization of the $${{\mathcal {N}}}=4$$

N
=
4

spinning particle to make it consistent in arbitrary dimensions.
Complex symmetric Toeplitz operators on the unit polydisk
Authors: Dong Xingtang , Gao Yongxin , Hu Qiuju
Published: December 2022

In this paper, we study the complex symmetry of Toeplitz operators on the weighted Bergman spaces over the unit polydisk. First, we completely characterize when anti-linear weighted composition operators [Formula: see text] are conjugations. We then give a sufficient and necessary condition for Toeplitz operators to be complex symmetric with respect to these conjugations. As a consequence, some interesting higher-dimensional complex symmetric phenomena appear on the unit polydisk such as the monomial Toeplitz operators [Formula: see text] with [Formula: see text] for some symmetric permutation matrix [Formula: see text]. Surprisingly, these operators [Formula: see text] are the only ones that are complex symmetric monomial Toeplitz operators on the unit bidisk.
The translational μ-τ reflection symmetry of Majorana neutrinos
Authors: Xing Zhi-Zhong
Published: December 2022

The present neutrino oscillation data allow [Formula: see text] (or [Formula: see text]) for the neutrino mass spectrum and support [Formula: see text] and [Formula: see text] as two good approximations for the PMNS lepton flavor mixing matrix [Formula: see text]. We show that these intriguing possibilities can be a very natural consequence of the translational[Formula: see text]-[Formula: see text] reflection symmetry — the effective Majorana neutrino mass term keeps invariant under the transformations [Formula: see text], [Formula: see text] and [Formula: see text] (for [Formula: see text] or 3), where [Formula: see text] is the charge conjugation of a constant spinor field [Formula: see text]. By extending such a working flavor symmetry to the canonical seesaw mechanism at a superhigh-energy scale, we calculate its soft breaking effects at the electroweak scale by using the one-loop renormalization-group equations.
Mapping Modern JVM Language Code to Analysis-Friendly Graphs: A Study with Kotlin
Authors: Li Lu , Liu Yan
Published: December 2022

Kotlin is a modern JVM language, gaining adoption rapidly and becoming Android official programming language. With its wide usage, the need for code analysis of Kotlin is increasing. Exposing code semantics explicitly with a properly structured format is the first step in code analysis and the construction of such representation is the foundation for downstream tasks. Recently, graph-based approaches became a promising way of encoding source code semantics. However, this work mainly focuses on representation learning with limited interpretability and shallow domain knowledge. The known evolvements of code semantics in new-generation programming languages have been overlooked. How to establish an effective mapping between naturally concise Kotlin source code with graph-based representation needs to be studied by analyzing known language features. Moreover, the feasibility of enhancing the mapping with code semantics automatically learned from the program needs to be explored. In this paper, we first propose a first-sight, rule-based mapping method, using composite representation with AST, CFG, DFG and language features. To examine the possibility of exposing code semantics in the mapped graph, we use Latent Semantic Indexing-based source code summarization to learn more features of each method, and then enrich the attributes of the corresponding node in the graph. We evaluate these mapping strategies with comparative experiments by simulating a code search solution as a downstream task. The experiment result shows that the graph-based method with built-in language features outperforms the text-based way without introducing greater complexity. Comparative experiments also prove that adding code semantics to the graph benefits the capacity of downstream tasks. When exploring the whole mapping process, our study explicitly revealed the practical barriers to extracting and exposing the hidden semantics from Kotlin source code, which may help enlighten source code representations for other modern languages.
The Flexible Cable Deformation Effect of a Prestressed Tuned Mass Damper on Vibration Control for Wind Turbine Towers
Authors: Lei Zhenbo , Liu Gang , Tang Wei , Li Mengzhu
Published: December 2022

Larger megawatt wind turbines are of significant height. The wind turbine tower (WTT) can suffer excessive vibration under external dynamic excitation, so an additional vibration control device is needed. Taking a novel prestressed tuned mass damper (PS-TMD) as the research object, its nonlinear vibration control performance induced by a flexible cable deformation effect was investigated. The dynamic coefficient amplitudes at two fixed points were derived based on the principle of virtual work, and results showed that the vibration amplitude considering flexible cable deformation is smaller than that of the linear PS-TMD system. For harmonic response, the numerical simulation of a 3.2 MW WTT indicated that vibration migration performance of the nonlinear PS-TMD is better than that of the linear PS-TMD. The Wilson-[Formula: see text] method was applied to analyze the vibration control effect under three fatigue and two ultimate wind loads. Results showed that the nonlinear PS-TMD can decrease the vibration amplitude more than the linear PS-TMD, and the vibration mitigation performance under the fatigue wind loads is slightly better than ultimate wind loads.
WHEN INTUITION FAILS: THE COMPLEX EFFECTS OF ASSIMILATIVE AND REPULSIVE INFLUENCE ON OPINION POLARIZATION
Authors: LIU SHUO , MÄS MICHAEL , XIA HAOXIANG , FLACHE ANDREAS
Published: December 2022

There is a public and scholarly debate about whether personalized services of social-media platforms contribute to the rise of bipolarization of political opinions. On the one hand, it is argued that personalized services of online social networks generate filter bubbles limiting contact between users who disagree. This reduces opportunities for assimilative social influence between users from different camps and prevents opinion convergence. On the other hand, empirical research also indicated that exposing users to content from the opposite political spectrum can activate the counter-part of assimilative influence, repulsive influence. Fostering contact that leads to opinion assimilation and limiting contacts likely to induce repulsive interactions, it has been concluded, may therefore prevent bipolarization. With an agent-based model, we demonstrate here that these conclusions fail to capture the complexity that assimilative and repulsive influence generate in social networks. Sometimes, more assimilative influence can actually lead to more and not less opinion bipolarization. Likewise, increasing the exposure of users to like-minded individuals sometimes intensifies opinion polarization. While emerging only in specific parts of the parameter space, these counter-intuitive dynamics are robust, as our simulation experiments demonstrate. We discuss implications for the debate about filter bubbles and approaches to improve the design of online social networks. While we applaud the growing empirical research on the micro-processes of assimilative and repulsive influence in online settings, we warn that drawing conclusions about resulting macro-outcomes like opinion bipolarization requires a rigorous analysis capturing the complexity of online communication systems. Intuition alone is error-prone in this context. Accordingly, models capturing the complexity of social influence in networks should play a more important role in the design of communication systems.
An Optimized Flower Categorization Using Customized Deep Learning
Authors: Rani Ritu , Pundhir Sandhya , Dev Amita , Sharma Arun
Published: December 2022

Categorizing flowers is quite a challenging task as there is so much diversity in the species, and the images of the different flower species could be pretty similar. Flower categorization involves many issues like low resolution and noisy images, occluded images with the leaves and the stems of the plants and sometimes even with the insects. The traditional handcrafted features were used for extraction of the features and the machine learning algorithms were applied but with the advent of the deep neural networks. The focus of the researchers has inclined towards the use of the non-handcrafted features for the image categorization tasks because of their fast computation and efficiency. In this study, the images are pre-processed to enhance the key features and suppress the undesired information’s and the objects are localized in the image through the segmentation to extract the Region of Interest, detect the objects and perform feature extraction and the supervised classification of flowers into five categories: daisy, sunflower, dandelion, tulip and rose. First step involves the pre-processing of the images and the second step involves the feature extraction using the pre-trained models ResNet50, MobileNet, DenseNet169, InceptionV3 and VGG16 and finally the classification is done into five different categories of flowers. Ultimately, the results obtained from these proposed architectures are then analyzed and presented in the form of confusion matrices. In this study, the CNN model has been proposed to evaluate the performance of categorization of flower images, and then data augmentation is applied to the images to address the problem of overfitting. The pre-trained models ResNet50, MobileNet, DenseNet169, InceptionV3 and VGG16 are implemented on the flower dataset to perform categorization tasks. The pre-trained models are empirically implemented and assessed on the various flower datasets. Performance analysis has been done in terms of the training, validation accuracy, validation loss and training loss. The empirical assessment of these pre-trained models demonstrate that these models are quite effective for the categorization tasks. According to the performance analysis, the VGG16 outperforms all the other models and provides a training accuracy of 99.01%. Densenet169 and MobileNet also give comparable validation accuracy. ResNet50 gives the lowest training accuracy of 60.46% as compared with the rest of the pre-trained replica or models.
Properties of Real Fuzzy Hilbert Adjoint Operator
Authors: Ghosal S. , Bag T.
Published: December 2022

Riesz representation theorem is established for fuzzy real sesquilinear form. Existence theorem and some properties of fuzzy real Hilbert adjoint operator are discussed.
Ranking Type-2 Intuitionistic Fuzzy Sets Based on Dice Similarity Measures
Authors: Annapurna N. , Sireesha V.
Published: December 2022

Ranking fuzzy numbers is an important part of decision-making in a fuzzy domain. Similarity measures are one of the widely used methods for sorting fuzzy numbers. In this paper, a Dice similarity measure is proposed for type-2 intuitionistic fuzzy sets (T2IFSs) and the properties of similarity measure are verified. The ranking in the proposed method is accomplished by comparing the given set to the best possible set under consideration. The proposed measure is tested on a wide range of T2IFSs and the results are analyzed with existing ranking methods. The comparison shows that the proposed method outperforms some of the shortcomings of existing ranking techniques and is thus effective in ranking.
Two Different Exits: Prediction and Performance of Stocks that are About to Stop Trading
Authors: Bai Ting , Hilscher Jens , Xiao Yitian
Published: December 2022

This paper predicts the two most common stock market exits — mergers and drops — using logit models based on firm-level variables and analyzes the returns of stocks that have high exit probabilities. Such analysis is important for investors given that frequent exits are partly responsible for the large US listing gap (Doidge et al., 2017). High merger probability stocks have positive 3-factor alphas and lower-than-average volatility. Firms with high drop probabilities have anomalously negative 3-, 4-, and 5-factor alphas between [Formula: see text]% and [Formula: see text]% per month. Results are robust to controlling for the effects of skewness, volatility, and turnover on returns.
DYNAMICAL MODELING AND ANALYSIS OF METHANE EMISSION ABATEMENT
Authors: SHUKLA J. B. , SUNDAR SHYAM , MISHRA ASHISH KUMAR , NARESH RAM
Published: December 2022

A nonlinear mathematical model is proposed and analyzed to study the effect of mitigation options on the control of methane emissions in the atmosphere caused by livestock and human populations so as to reduce global warming. Livestock population is one of the main agricultural sources of greenhouse gases in the world. It is assumed that the atmospheric concentration of methane increases in the atmosphere due to cumulative density of methane formed by various processes involved in the farming of livestock populations. Various human activities are also significant contributors to methane emissions. The most notable effects of global warming around the world include the progressive heating of the Earth’s surface, oceans and atmosphere; glacier melting; and various diseases. Mitigation options are applied to control the methane emissions considerably in the atmosphere caused by livestock and human populations which in turn reduces the effects of global warming. The data from model prediction is compared with actual methane data in the atmosphere and found to be fairly close.
Preference-aware Graph Attention Networks for Cross-Domain Recommendations with Collaborative Knowledge Graph
Authors: Li Yakun , Hou Lei , Li Juanzi
Published: December 2022

Knowledge graphs (KGs) can provide users with semantic information and relations among numerous entities and nodes, which can greatly facilitate the performance of recommender systems. However, existing KG-based approaches still suffer from severe data sparsity and may not be effective in capturing the preference features of similar entities across domains. Therefore, in this article, we propose a
P
reference-aware
G
raph
A
ttention network model with
C
ollaborative
K
nowledge
G
raph (
PGACKG
) for cross-domain recommendations. Preference-aware entity embeddings with some collaborative signals are first obtained by exploiting the graph-embedding model, which can transform entities and items in the collaborative knowledge graph into semantic preference spaces. To better learn user preference features, we devise a preference-aware graph attention network framework that aggregates the preference features of similar entities within domains and across domains. In this framework, multi-hop reasoning is employed to assist in the generation of preference features within domains, and the node random walk based on frequency visits is proposed to gather similar preferences across domains for target entities. Then, the final preference features of entities are fused, while a novel
C
ross-domain
B
ayesian
P
ersonalized
R
anking (
CBPR
) is proposed to improve cross-domain recommendation accuracy. Extensive empirical experiments on four real-world datasets demonstrate that our proposed approach consistently outperforms state-of-the-art baselines. Furthermore, our PGACKG achieves strong performance in different ablation scenarios, and the interaction sparsity experiments also demonstrate that our proposed approach can significantly alleviate the data sparsity issue.
Improving Workflow Integration with xPath: Design and Evaluation of a Human-AI Diagnosis System in Pathology
Authors: Gu Hongyan , Liang Yuan , Xu Yifan , Williams Christopher Kazu , Magaki Shino , Khanlou Negar , Vinters Harry , Chen Zesheng , Ni Shuo , Yang Chunxu , Yan Wenzhong , Zhang Xinhai Robert , Li Yang , Haeri Mohammad , Chen Xiang ‘Anthony’
Published: December 2022

Recent developments in AI have provided assisting tools to support pathologists’ diagnoses. However, it remains challenging to incorporate such tools into pathologists’ practice; one main concern is AI’s insufficient workflow integration with medical decisions. We observed pathologists’ examination and discovered that the main hindering factor to integrate AI is its incompatibility with pathologists’ workflow. To bridge the gap between pathologists and AI, we developed a human-AI collaborative diagnosis tool—
xPath
 —that shares a similar examination process to that of pathologists, which can improve AI’s integration into their routine examination. The viability of
xPath
 is confirmed by a technical evaluation and work sessions with 12 medical professionals in pathology. This work identifies and addresses the challenge of incorporating AI models into pathology, which can offer first-hand knowledge about how HCI researchers can work with medical professionals side-by-side to bring technological advances to medical tasks towards practical applications.