Spectral Properties Research Articles

Two transitions in complex eigenvalue statistics: Hermiticity and integrability breaking

Open quantum systems have complex energy eigenvalues which are expected to follow non-Hermitian random matrix statistics, when chaotic, or two-dimensional (2d) Poisson statistics, when integrable. We investigate the spectral properties of a many-body quantum spin chain, i.e., the Hermitian Heisenberg model with imaginary disorder. Its rich complex eigenvalue statistics is found to separately break both Hermiticity and integrability at different scales of the disorder strength. With no disorder, the system is integrable and Hermitian, with spectral statistics corresponding to the 1d Poisson point process. At very small disorder, we find a transition from 1d Poisson statistics to an effective D-dimensional Poisson point process, showing Hermiticity breaking. At intermediate disorder, we find integrability breaking, as inferred from the statistics matching that of non-Hermitian complex symmetric random matrices in class AI†. For large disorder, as the spins align, we recover the expected integrability (now in the non-Hermitian setup), indicated by 2d Poisson statistics. These conclusions are based on fitting the spin-chain data of numerically generated nearest- and next-to-nearest-neighbor spacing distributions to an effective 2d Coulomb gas description at inverse temperature β. We confirm that such an effective description of random matrices also applies in classes AI† and AII† up to next-to-nearest-neighbor spacings. Published by the American Physical Society 2025

Spectral Properties of The Finite System of Klein-Gordon S-Wave Equations with Condition Depends on Spectral Parameter

The spectral characteristics of the operator L is studied where L is defined within the Hilbert space L2(R+,CV ) given by a finite system of Klein-Gordon type differential equations and boundary condition depends on spectral parameter. The research of the Klein-Gordon type operator continues to be an important topic for researchers due to the range of applicability of them in numerous branches of mathematics and quantum physics. Contrary to the previous works, we take the potential as complex valued and generalize the problem to the matrix Klein-Gordon operator case. The spectrum is derived by determining the Jost function and resolvent operator of the prescribed operator. Further, we provide the conditions that must be met for the certain quantitative properties of the spectrum.

Asymptotic Periodicity of Bounded Mild Solutions for Evolution Equations with Non-Densely Defined and Fractional Derivative

In the present article, we establish conditions for the asymptotic periodicity of bounded mild solutions in two distinct cases of evolution equations. The first class involves non-densely defined operators, while the second class incorporates densely defined operators with fractional derivatives that generate a semigroup of contractions. Our method integrates the theory of spectral properties of uniformly bounded continuous functions defined on the positive real semi-axis. Additionally, we apply extrapolation theory to evolution equations with non-densely defined operators. To illustrate our main results, we provide a concrete example.

Light Absorbing Particles Deposited to Snow Cover Across the Upper Colorado River Basin, Colorado, 2013–2016: Interannual Variations From Multiple Natural and Anthropogenic Sources

AbstractAtmospheric particulate matter (PM) as light‐absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013–2016) from the mountainous Upper Colorado River basin by comparing among laboratory‐measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35–2.50 μm, varied by a factor of 1.9 (range, 0.2300–0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6–22.5 wt. %) including inferred black carbon, natural organic matter, and carbon‐based synthetic, black road‐tire‐wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11–0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source‐area contributions implying strong interannual changes in regional source behavior, dust‐storm frequency, and (or) transport tracks. Observations of dust‐storm activity in the western U.S. and particle‐size averages for all samples (median, 25 μm) indicated that regional dust from deserts dominated mineral‐dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

Clinical and molecular characteristics and long-term outcomes of pediatric intracranial meningiomas: a comprehensive analysis from a single neurosurgical center

BackgroundMeningioma represents the most common intracranial tumor in adults. However, it is rare in pediatric patients. We aimed to demonstrate the clinicopathological characteristics and long-term outcome of pediatric meningiomas (PMs).MethodWe enrolled 74 patients with intracranial PMs and analyzed their clinicopathological characteristics. Targeted next generation sequencing was used to detect alterations in meningioma relevant genes. Progression-free survival (PFS) was compared between PMs and adult meningiomas (AMs). Univariate and multivariate Cox analyses were employed to evaluate the predictive values of clinicopathological characteristics. A nomogram was constructed and its predictive accuracy evaluated.Result40 females (54.1%) and 34 males (45.9%) patients, with the gender ratio of 1.18:1, were identified. 9 (12.2%) cases were clinically diagnosed as NF2-related Schwannomatosis (NF2-SWN), while 65 (87.8%) were sporadic. Ventricular location was found in 16 patients (21.6%). 19 patients (25.7%) experienced recurrence during a median follow-up period of 33 months (range 2 -145.25 months). The 3-, 5-, and 8-year PFS rates was 74.74%, 74.74%, and 59.38%, respectively. The PFS of the PM and AM cohorts were not significantly different, with or without propensity score matching. NF2 mutation was observed in 33 sporadic PMs (52.4%), whereas alterations in other genes (AKT1, TRAF7, SMO, PIK3CA, KLF4) frequently mutated in AMs, were not identified. The proportion of NF2 mutation in PMs was significantly lower in the skull base than other locations (p = 0.02). One anaplastic PM harbored TERT promoter mutation. Of note, in sporadic PMs, NF2 mutations were not significantly associated with PFS (p = 0.434) or overall survival (OS) (p = 0.60). The multivariate Cox analysis showed NF2-SWN (p < 0.001) and extent of resection (p = 0.013) to be independently associated with the PFS of PMs. Our prognostic model showed predictive accuracy for long-term PFS in PMs as the 3-, 5- and 8-year Area Under the Curve (AUC) was 0.927, 0.930, and 0.870, respectively.ConclusionPM was characterized by its relative male predominance, ventricular location, NF2-SWN, and NF2 mutation. Of note, PMs had similar prognosis to AMs and NF2 alteration was not significantly associated with PFS in PMs.

Adjuvant radiation improves survival outcomes in adrenocortical carcinoma: A population-based study.

The aim of this study was to evaluate the clinical benefits and outcomes of adjuvant radiation therapy on adrenocortical carcinoma (ACC) patients. All patients with ACC that were reported between 2010 and 2015 were identified from the Surveillance, Epidemiology, and End Results database. A forward-stepwise Cox proportional hazards regression was used to identify independent risk factors. A new nomogram was created to predict overall and cancer-free survival probabilities at 1, 3, and 5 years for ACC patients. The concordance index, the area under the receiver operating characteristic curve, calibration curves, and decision curve analysis were used to validate the accuracy and reliability of the model. A total of 426 ACC patients were enrolled in this study, of which 84 (19.7%) cases underwent adjuvant radiation therapy (RT). Six factors (age, T stage, type of surgery, radiation, and bone and liver metastases) were significantly related to overall survival (OS) (P < .05). Five factors (T stage, type of surgery, radiation, and bone and liver metastases) were significantly related to cancer-specific survival (CSS) (P < .05). A nomogram for OS and CSS was constructed. The area under the receiver operating characteristic curve values for 1-, 3-, and 5-year OS were 0.85, 0.818, and 0.814, respectively, and for CSS, they were 0.839, 0.803, and 0.796, respectively. C-indices were 0.756 and 0.749 for OS and CSS, respectively, indicating that the nomograms for OS and CSS had satisfactory discriminative power. A good consistency between the observed and the predicted survival was found in the calibration curves, and the nomogram has a good net clinical benefit, which is presented in the decision curve analysis curves. Our study demonstrates that adjuvant RT can produce a significant improvement in survival outcomes for ACC patients and suggests that adjuvant RT should routinely be applied in ACC patients.

Increased nerve density adversely affects outcome in colorectal cancer and denervation suppresses tumor growth

BackgroundThe colon and rectum are highly innervated, with neural components within the tumor microenvironment playing a significant role in colorectal cancer (CRC) progression. While perineural invasion (PNI) is associated with poor prognosis in CRC, the impact of nerve density and diameter on tumor behavior remains unclear. This study aims to evaluate the prognostic value of nerve characteristics in CRC and to verify the impact of nerves on tumor growth.MethodsTissue samples from 129 CRC patients were stained with immunofluorescent markers NF-L and S100B to detect nerves. Nerve diameter and density were measured and normalized. Kaplan-Meier survival analysis and Cox regression models were used to identify prognostic factors. Prognostic models were established using receiver operating characteristic (ROC) curve analysis to assess the predictive value of neural factors. A murine chemical denervation model was employed to disrupt sympathetic nerves using 6-hydroxydopamine, inhibit muscarinic receptor 3 with darifenacin, and ablate sensory neurons with capsaicin.ResultsThe total nerve density was 0.72 ± 0.59/mm², with intratumoral (0.42 ± 0.40/mm²) being significantly lower than extratumoral regions (1.00 ± 0.75/mm²). The average nerve diameter was 28.14 ± 6.04 μm, with no significant difference between intratumoral (28.2 ± 7.65 μm) and extratumoral regions (27.86 ± 6.72 μm). PNI was observed in 65 patients (50.4%). PNI and high normalized nerve density (NND) were associated with shorter overall survival and disease-free survival in CRC patients, with PNI identified as an independent prognostic factor. Patients with PNI exhibit higher NND. Incorporating PNI and NND into ROC curve analysis improved the sensitivity and specificity of survival predictions. In the murine model, chemical denervation of sympathetic, parasympathetic, and sensory nerves significantly reduced rectal tumor volume.ConclusionsPNI and NND are critical factors influencing CRC patient survival and enhance the accuracy of survival prediction models. Moreover, chemical denervation effectively inhibits rectal tumor growth in vivo, highlighting the potential of neural targeting as a therapeutic strategy in CRC.

Spectral properties of $$\mathcal {C}$$-graphs

Spectral properties of $$\mathcal {C}$$-graphs

Transient cortical beta-frequency oscillations associated with contextual novelty in high density mouse EEG

Beta-frequency oscillations (20–30 Hz) are prominent in both human and rodent electroencephalogram (EEG) recordings. Discrete epochs of beta (or Beta2) oscillations are prevalent in the hippocampus and other brain areas during exploration of novel environments. However, little is known about the spatial distribution and temporal relationships of beta oscillations across the cortex in response to novel contexts. To investigate this, mice fitted with 30-channel EEG-style multi-electrode arrays underwent a single recording session in a novel environment. While changes to spectral properties of cortical oscillations were minimal, there was a profound increase in the rate of beta bursts during the initial part of the recording session, when the environment was most novel. This was true across the cortex but most notable in recording channels situated above the retrosplenial cortex. Additionally, novelty was associated with greater connectivity between retrosplenial areas and the rest of the cortex, specifically in the beta frequency range. However, it was also found that the cortex in general, is highly modulated by environmental novelty. This data further suggests the retrosplenial cortex is an important hub for distinguishing environmental context and highlights the diversity of functions for beta oscillations across the brain, which can be observed using high-density EEG.

Crystal growth, spectral properties, and 2.3 µm continuous-wave laser operation of Tm:YScO3 and Tm:LuScO3 crystals

Crystal growth, spectral properties, and 2.3 µm continuous-wave laser operation of Tm:YScO3 and Tm:LuScO3 crystals

A Systematic Review: The Role of Artificial Intelligence in Lung Cancer Screening in Detecting Lung Nodules on Chest X-Rays

Background: Lung cancer remains one of the leading causes of cancer-related deaths worldwide. Artificial intelligence (AI) holds significant potential roles in enhancing the detection of lung nodules through chest X-ray (CXR), enabling earlier diagnosis and improved outcomes. Methods: Papers were identified through a comprehensive search of the Web of Science (WOS), Scopus, and Ovid Medline databases for publications dated between 2020 and 2024. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 34 studies that met the inclusion criteria were selected for quality assessment and data extraction. Results: AI demonstrated sensitivity rates of 56.4–95.7% and specificities of 71.9–97.5%, with the area under the receiver operating characteristic (AUROC) values between 0.89 and 0.99, compared to radiologists’ mean area under the curve (AUC) of 0.81. AI performed better with larger nodules (&gt;2 cm) and solid nodules, showing higher AUC values for calcified (0.71) compared to non-calcified nodules (0.55). Performance was lower in hilar areas (30%) and lower lung fields (43.8%). A combined AI-radiologist approach improved overall detection rates, particularly benefiting less experienced readers; however, AI showed limitations in detecting ground-glass opacities (GGOs). Conclusions: AI shows promise as a supplementary tool for radiologists in lung nodule detection. However, the variability in AI results across studies highlights the need for standardized assessment methods and diverse datasets for model training. Future studies should focus on developing more precise and applicable algorithms while evaluating the effectiveness and cost-efficiency of AI in lung cancer screening interventions.

GRB 241107A: A Giant Flare from a Close-by Extragalactic Magnetar?

Abstract We report the results on the short gamma-ray burst GRB 241107A, obtained with the IBIS instrument on board the INTEGRAL satellite. The burst had a duration of about 0.2 s, a fluence of 8 × 10−7 erg cm−2 in the 20 keV–10 MeV range, and a hard spectrum, characterized by a peak energy of 680 keV. The position of GRB 241107A has been precisely determined because it fell inside the imaging field of view of the IBIS coded mask instrument. The presence of the nearby galaxy PGC 86046 in the 3′ radius error region suggests that GRB 241107A might be a giant flare from a magnetar rather than a canonical short gamma-ray burst. For the 4.1 Mpc distance of PGC 86046, the isotropic energy of 1.6 × 1045 erg is in agreement with this hypothesis, which is also supported by the time-resolved spectral properties similar to those of the few other extragalactic magnetars giant flares detected so far.

Bath dynamical decoupling with a quantum channel

Abstract Bang–bang dynamical decoupling protects an open quantum system from decoherence due to its interaction with the surrounding bath/environment. In its standard form, this is achieved by strongly kicking the system with cycles of unitary operations, which average out the interaction Hamiltonian. In this paper, we generalize the notion of dynamical decoupling to repeated kicks with a quantum channel, which is applied to the bath. We derive necessary and sufficient conditions on the employed quantum channel and find that bath dynamical decoupling works if and only if the kick is ergodic. Furthermore, we study in which circumstances completely positive trace-preserving (CPTP) kicks on a mono-partite quantum system induce quantum Zeno dynamics with its Hamiltonian cancelled out. This does not require the ergodicity of the kicks, and the absence of decoherence-free subsystems is both necessary and sufficient. While the standard unitary dynamical decoupling is essentially the same as the quantum Zeno dynamics, our investigation implies that this is no longer true in the case of CPTP kicks. To derive our results, we prove some spectral properties of ergodic quantum channels, that might be of independent interest. Our approach establishes an enhanced and unified mathematical understanding of several recent experimental demonstrations and might form the basis of new dynamical decoupling schemes that harness environmental noise degrees of freedom.

Diurnal and daily fluctuations in levels of the urinary oxidative stress marker 8-hydroxyguanosine in spot urine samples

BackgroundUrinary 8-hydroxyguanosine (8-OHGuo) levels serve as a biomarker for oxidative stress and hydroxyl radical–induced RNA damage. Evaluating the diurnal and daily fluctuations in urinary 8-OHGuo excretion levels is essential for understanding its implications. However, research in this area remains limited. In this study, we aim to investigate the diurnal and daily fluctuations in 8-OHGuo levels as well as the factors that influence these variations, using spot urine samples.MethodsUrine samples were collected from seven healthy participants during each urination from the time of awakening until 24:00 h to evaluate diurnal variations. To assess daily fluctuations, urine samples were collected from 18 healthy participants at the time of awakening for 23 consecutive days. The urinary 8-OHGuo levels were measured using an HPLC-ECD method.ResultsNo significant variations were observed in the diurnal levels of urinary 8-OHGuo among non-smokers. Conversely, the daily variation of 8-OHGuo in the urine of the smoker was significant, with a coefficient of variation of 18.71%. Each individual maintained a characteristic value despite some diurnal fluctuations. Furthermore, the daily levels of 8-OHGuo exhibited a range of variations influenced by lifestyle factors, including mental state, sleep duration, smoking, menstrual cycle, and dietary habits.ConclusionAs a specific marker of RNA oxidation, 8-OHGuo provides unique insights distinct from those provided by the widely used DNA oxidation marker 8-hydroxydeoxyguanosine as an indicator of oxidative stress. Urinary 8-OHGuo could serve as a valuable biomarker for managing and preventing oxidative stress–related diseases, provided that the specific range of daily variations is established. The high daily variation in urinary 8-OHGuo levels necessitates the use of multiple samples to accurately determine individual levels. However, further research with large sample sizes will help to validate these findings.

Single-Flow Automated Line with Intermediate Storage and Various Types of Downtime of Production Cells

In technology we widely use semi-Markov processes, because with their help someone can model a large number of production systems. For increasing automated production flexibility and reliability workers use storage devices in different roles, such as inter- operational buffers in conveyor production, as loading and unloading solutions, as modules with the ability to store products, etc. On the other hand, during operation, off-cycle time losses (downtime) occur, which have a significant impact on the system. In this regard, problems arise in constructing mathematical models based on them, taking into account the features, structure and purpose of such systems, making it possible to identify and analyze those types of downtime that have the greatest impact on their functioning. It is known that in practice we cannot completely eliminate any type of downtime during operation, so the our research goal is to develop a mathematical model that will allow us to determine by what amount certain downtime can actually be reduced and how this will effect on the reliability and efficiency characteristics. In this paper, for a single-threaded automated line with intermediate storage devices, we build a semi-Markov model with a discrete-continuous phase state space. Then, using the asymptotic phase enlargement algorithm, we find expressions for the approximate calculation of the system under consideration stationary reliability characteristics. In the final part of the article, as an illustration of our results, we present the calculated stationary characteristics values using the example of a three-phase system for different processing times of the outlet device.

Floquet topological phase transitions in 2D Su-Schrieffer-Heeger model: Interplay between time reversal symmetry breaking and dimerization

Abstract In this paper, we present a theoretical analysis of 2D Su-Schrieffer-Heeger (SSH) model within the context&amp;#xD;of Floquet topological insulators (FTIs). Generally speaking, FTIs are endowed with time reversal symmetry&amp;#xD;(TRS) and its breaking by means of a time periodical process triggers a topological phase transition governed by&amp;#xD;a Chern number. In our proposed model, the condition of TRS breaking is achieved by circularly polarized light&amp;#xD;irradiation. The 2D SSH system represents actually a square lattice, where the first order neighbors hopping is&amp;#xD;realized only on horizontal and vertical directions. One of the most important findings of our work is that the&amp;#xD;TRS breaking is forbidden in the absence of diagonal hopping (between second order neighbors) and we give&amp;#xD;a pure analytical proof. On the other hand, due to Peierls transition (PT) (dimerization), the 2D SSH model&amp;#xD;undergoes a specific topological transition governed by a Zak phase. Going further, we pursue the interplay&amp;#xD;between the TRS breaking and PT. We find thus an interesting topological frustration which is lifted upon PT.&amp;#xD;The results are supported both analytically and numerically in terms of Chern numbers, spectral properties,&amp;#xD;chiral edge states localization and Hall transport simulations. Our model is suitable not only for condensed&amp;#xD;matter (materials), but also for cold gasses trapped in optical lattices or electric circuits.

Studying the effect of concentration on spectral and optical properties of chitosan polymer

Due to its noteworthy physico-chemical behaviors, the chitosan (CS) biopolymer presents a compelling alter-native to conventional biomaterials. By measuring the emission spectra at a spectrofluorophotometer in differ-ent concentrates (1x10-4, 1x10-5, and 1x10-6) M, the spectral characteristics of the CS polymer were obtained. The crystallinity of the CS polymer was determined by X-ray diffraction (XRD) analysis, which shows only one dominant peak indexed to the orthorhombic structure. With a drop in solution concentration, there was a shift toward the shorter wavelength and a decline in quantum yield. Using a UV-Vis spectrophotometer, the optical properties of the CS polymer, including its refractive index, absorption coefficient, energy band gap, extinction coefficient, and dielectric constant, have been studied. It was observed through the results that the optical parameters are linearly dependent with concentration. In contrast to the optical energy gap, which de-creases with increasing concentration.

Investigating the factors influencing teachers’ adoption of gamification strategies in higher education: insights from Korthagen’s onion model

PurposeInterest in gamification as a relevant and innovative pedagogical tool has increased in recent years among academics and educators. While considerable literature has focused on the effectiveness of gamified learning, little is known about the motivations behind its adoption. By examining teachers’ perspectives, which are often overlooked, we investigated the factors influencing teachers’ adoption of gamification strategies.Design/methodology/approachWe adopted Korthagen’s onion model as the main theoretical lens to identify the influencing factors. A qualitative study involving interviews with 15 French higher education teachers was conducted to achieve our purpose.FindingsThe results were organized within the six layers of the onion model, through which we demonstrated the factors influencing teachers’ adoption of gamification. The institutional environment and teachers’ internal characteristics (beliefs, values, identity and mission) were identified as the determinants of gamification use.Originality/valueUnlike most gamification studies, this research contributes to the literature by considering teachers’ perspectives and integrating the Korthagen model into the educational setting. We also propose an integrative theoretical approach that uncovers synergies between the Korthagen model and the educational leadership literature.

Upstreamness and downstreamness in input–output analysis from local and aggregate information

Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input–output (I–O) tables. In this work, we show that an accurate estimation of the role played by sectors and countries in supply chain networks can be achieved without full knowledge of the I–O tables, but only relying on local and aggregate information, e.g., the total intermediate demand per sector. Our method, based on a rank-1 approximation to the I–O table, shows consistently good performance in reconstructing rankings (i.e., upstreamness and downstreamness measures for countries and sectors) when tested on empirical data from the world input–output database. Moreover, we connect the accuracy of our approximate framework with the spectral properties of the I–O tables, which ordinarily exhibit relatively large spectral gaps. Our approach provides a fast and analytically tractable framework to rank constituents of a complex economy without the need of matrix inversions and the knowledge of finer intersectorial details.

Linear Matrix Inequality‐based design of distributed proportional‐integral‐derivative for the output consensus tracking in heterogeneous high‐order multi‐agent systems

AbstractThis article addresses the cooperative output consensus tracking problem for high‐order heterogeneous multi‐agent systems via a distributed proportional‐integral‐derivative (PID)‐like control strategy and proposes two novel control methodologies for the tuning of the control gains, which do not require any assumption and/or limitation on agent system modeling. By extending the static output feedback (SOF) paradigm to distributed domain, the asymptotic stability problem for the overall MAS composed of agents is revisited into decoupled stabilization problems to be solved. Then, by exploiting the Lyapunov and matrix theory, the typical SOF bilinear matrix inequality (BMI)‐based stability conditions are recast into feasible linear matrix inequality (LMI)‐based ones, whose solutions allow finding the proper values of the PID control gains ensuring the achievement of the cooperative task. In doing so, the proposed procedures reduce the computational effort required for the control design, hence providing a greater attraction for a wider range of practical engineering applications. The scalability and the adaptability of the proposed control methodology in solving an alternative cooperative control problem in the presence of multiple leaders, that is, the output containment task, are also analytically investigated. Numerical simulations confirm the effectiveness of the theoretical derivations.