Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of frequency chirping and extinction ratio of optical phase conjugate signals by four-wave mixing in SOA's

We present a complete large-signal dynamic model of a wavelength converter or optical phase conjugator based on four-wave mixing in semiconductor optical amplifiers. The modified transfer matrix method (TMM) is used for implementing the large-signal dynamic model. It is possible for this model to involve not only forward traveling waves, but also backward traveling waves. Also, this model includes longitudinal variation of carrier-induced reflective index, /spl alpha/-parameter, gain, carrier density, photon density, reflection, and amplified spontaneous emission noise at each small section. Therefore, we can accurately evaluate frequency chirping, optical pulse pattern, and extinction ratio of the conjugate signal. Th eye-opening penalty has been calculated to investigate the effects of frequency chirping and extinction ratio on transmission performance.
The Analysis of Economic Time Series

T HE PROBLEM of the analysis of economic time series has occupied the attention of a great number of economists, mathematicians and statisticians, since the time when a considerable amount of statistical data became available in this field. It is probably one of the most unfortunate circumstances for our science that most economic data come in the shape of time series. Hence they cannot easily be dealt with by the ordinary statistical methods which have proven useful in other statistical applications, especially in physics and biology. The most important reason these methods are inapplicable is very simple to understand. Items of data which are ordered in time are in general not mutually independent or random in time. They violate one of the most significant assumptions required in the application of probability theory on which all modern statistical tools are founded. Possible methods of analyzing interrelated statistical events have not yet been very fully explored, in spite of the fact that some progress has been made especially by the Russian school of probability. (Markoff chains.') In practical statistical problems as distinguished from theoretical probability questions, we are far from satisfactory solutions. Other features may also be present, which make the application of statistical methods difficult. The variance of the population, for instance, may not be constant in time.2 There are two problems to be distinguished in the analysis of economic time series. The first is one which this material has in common with all other statistical data. This first problem is an investigation of the random character of the data, e.g., the separation of the random and the non-random parts of time series. There are still many workers in the field of economic statistics who fail to realize fully the great importance of this problem. It arises from the fact that only an answer to the question of what is and what is not random in a time series can
Detonation ignition from a temperature gradient for a two-step chain-branching kinetics model

The evolution from a linear temperature gradient to a detonation is investigated for combustible materials whose chemistry is governed by chain-branching kinetics, using a combination of high-activation-temperature asymptotics and numerical simulations. A two-step chemical model is used, which captures the main properties of detonations in chain-branching fuels. The first step is a thermally neutral induction time, representing chain initiation and branching, which has a temperature-sensitive Arrhenius form of the reaction rate. At the end of the induction time is a transition point where the fuel is instantaneously converted into chain-radicals. The second step is the main exothermic reaction, representing chain termination, assumed to be temperature insensitive. Emphasis is on comparing and contrasting the results with previous studies that used simple one-step kinetics. It is shown that the largest temperature gradient for which a detonation can be successfully ignited depends on the heat release rate of the main reaction. The slower the heat release compared to the initial induction time, the shallower the gradient has to be for successful ignition. For example, when the rate of heat release is moderate or slow on the initial induction time scale, it was found that the path of the transition point marking the end of the induction stage should move supersonically, in which case its speed is determined only by the initial temperature gradient. For steeper gradients such that the transition point propagates subsonically from the outset, the rate of heat release must be very high for a detonation to be ignited. Detonation ignition for the two-step case apparently does not involve the formation of secondary shocks, unlike some cases when one-step kinetics is used.
Laboratory Measurements of Fe XXIV Line Emission: 3 → 2 Transitions near Excitation Threshold

Using the Electron Beam Ion Trap facility at Lawrence Livermore National Laboratory, we have measured relative cross sections for Fe XXIV line emission at electron energies between 0.7 and 3.0 keV. The measurements include line formation by direct electron impact excitation (DE), radiative cascades, resonant excitation (RE), and dielectronic recombination (DR) satellites with captured electrons in n≥5 levels. Good agreement with R-matrix and distorted wave calculations is found. In collisionally ionized plasmas, at temperatures near where the ion abundance peaks (kTe~1.7 keV), the RE contributions arefound to be ≲5% of the line emission, while the DR satellites contribute ≲10%. While good agreement with state-of-the-art atomic physics calculations is found, there is less good agreement with existingspectral synthesis codes in common astrophysical use. For the Fe XXIV 3p3/2→2s1/2, 3p1/2→2s1/2, and 3d5/2→2p3/2 transitions, the synthesis code MEKAL underestimates the emissivity in coronal equilibrium by ~20% at temperatures near where the ion abundance peaks. In situations where the ionization balance is not solely determined by the electron temperature, RE and DR satellites may contribute a considerable fraction of the line emission.
Ethanol Metabolism and Melanoma

Simple Summary Acetaldehyde (AcAH) is a carcinogenic byproduct of ethanol metabolism. Ethanol-associated malignancies commonly occur in the upper gastrointestinal tract exposed to AcAH after ethanol ingestion. Unexpectedly but true, emerging epidemiological evidence supports a link between alcohol consumption and cutaneous melanoma, suggesting skin exposure to ethanol and AcAH as potential causes of skin cancer. Humans are unavoidably exposed to ethanol and AcAH daily in multiple ways, such as through alcohol consumption, food ingestion, inhalation, skin contact, and bodily microbiota. This review examines the sources of ethanol and AcAH in the skin, their metabolic pathways, and the consequences of dysfunctional ethanol and AcAH metabolizing enzymes, focusing on the role of these factors in melanoma development and progression. Abstract Malignant melanoma is the deadliest form of skin cancer. Despite significant efforts in sun protection education, melanoma incidence is still rising globally, drawing attention to other socioenvironmental risk factors for melanoma. Ethanol and acetaldehyde (AcAH) are ubiquitous in our diets, medicines, alcoholic beverages, and the environment. In the liver, ethanol is primarily oxidized to AcAH, a toxic intermediate capable of inducing tumors by forming adducts with proteins and DNA. Once in the blood, ethanol and AcAH can reach the skin. Although, like the liver, the skin has metabolic mechanisms to detoxify ethanol and AcAH, the risk of ethanol/AcAH-associated skin diseases increases when the metabolic enzymes become dysfunctional in the skin. This review highlights the evidence linking cutaneous ethanol metabolism and melanoma. We summarize various sources of skin ethanol and AcAH and describe how the reduced activity of each alcohol metabolizing enzyme affects the sensitivity threshold to ethanol/AcAH toxicity. Data from the Gene Expression Omnibus database also show that three ethanol metabolizing enzymes (alcohol dehydrogenase 1B, P450 2E1, and catalase) and an AcAH metabolizing enzyme (aldehyde dehydrogenase 2) are significantly reduced in melanoma tissues.
Closed-form expressions for distribution of sum of exponential random variables

In many systems which are composed of components with exponentially distributed lifetimes, the system failure time can be expressed as a sum of exponentially distributed random variables. A previous paper mentions that there seems to be no convenient closed-form expression for all cases of this problem. This is because in one case the expression involves high-order derivatives of products of multiple functions. The authors prove a simple intuitive multi-function generalization of the Leibnitz rule for high-order derivatives of products of two functions and use this to simplify this expression, thus giving a closed form solution for this problem. They similarly simplify the state-occupancy probabilities in general Markov models.
Blockchain-Based Swarm Learning for the Mitigation of Gradient Leakage in Federated Learning

Federated Learning (FL) is a machine learning technique in which collaborative and distributed learning is performed, while the private data reside locally on the client. Rather than the data, only gradients are shared among all collaborative nodes with the help of a central server. To ensure the data privacy, the gradients are prone to the deformation, or the representation is perturbed before sharing, ultimately reducing the performance of the model. Recent studies show that the original data can still be recovered using latent space (i.e., gradient leakage problem) by Generative Adversarial Network and different optimization algorithms such as Bayesian and Covariance Matrix Adaptation Evolution Strategy. To address the issues of data privacy and gradient leakage, in this paper, we train deep neural networks by exploiting the blockchain-based Swarm Learning (SL) framework. In the SL scheme, instead of sharing perturbed or noisy gradients to the central server, we share the original gradients among authenticated (i.e., blockchain-based smart contract) training nodes. To demonstrate the effectiveness of the SL approach, we evaluate the proposed approach using the standard CIFAR10 and MNIST benchmark datasets and compare it with the other existing methods.
Testing Constancy for Isotonic Regressions

Abstract. In this paper, we propose a bootstrap method for testing the constancy of an isotonic regression. The technique we develop is completely non‐parametric and enlarges the appli‐cability of the classical chi‐bar‐squared tests, which require normality assumptions. We prove that our procedure is asymptotically correct and consistent. Moreover, by means of simulations we show that it behaves suitably in practice, and similarly to the chi‐bar‐squared tests under normality. Finally, we illustrate the method with the study of a real case that is well known in the related literature.
Coupled mode theory: a powerful tool for analyzing complex VCSELs and designing advanced device features

Vertical-cavity surface-emitting lasers (VCSELs) have become leading light sources in plenty of applications due to their good characteristics and low costs. There are, however, some features that need improvements; therefore, optimized or new designs ideas are necessary. To this aim, an electromagnetic simulation tool, which is fast and precise at the same time, is desirable; to cover all the possible requirements, it should be fully three-dimensional (3-D) and vectorial. A model with such features was first proposed by Bava et al. ("Three-Dimensional Model for Vectorial Fields in Vertical-Cavity Surface-Emitting Lasers", Phys. Rev. A, vol. 63, p. 23816, 2001), based on coupled-mode theory. Here, a review of its applications will be given, related to particular devices: nonperfectly circular VCSELs and phase-coupled arrays. The comparison with the corresponding experimental results turns out to be very satisfactory. Therefore, we were encouraged to use the model for obtaining design criteria of polarization maintaining VCSELs by using a small relief grating. The capability of gratings to pin the VCSEL polarization was already demonstrated; however, the different configurations do not allow one to have a clear overview of this technique. Moreover, to the best of our knowledge, a full simulation of a VCSEL with a grating was never presented, due to the complexity of treating the corresponding fully 3-D and vectorial problem. For the first time, we have the possibility of comparing different configurations on the same footing; in particular, we will evaluate the performances of dielectric and metal gratings. With the design we propose here, single-transverse and single-polarization-mode operation are predicted with a suppression of the other polarization easily in the order of 45 dB.
Diagnosis of Optic Disc Oedema: Fundus Features, Ocular Imaging Findings, and Artificial Intelligence

ABSTRACT Optic disc swelling is a manifestation of a broad range of processes affecting the optic nerve head and/or the anterior segment of the optic nerve. Accurately diagnosing optic disc oedema, grading its severity, and recognising its cause, is crucial in order to treat patients in a timely manner and limit vision loss. Some ocular fundus features, in light of a patient’s history and visual symptoms, may suggest a specific mechanism or aetiology of the visible disc oedema, but current criteria can at most enable an educated guess as to the most likely cause. In many cases only the clinical evolution and ancillary testing can inform the exact diagnosis. The development of ocular fundus imaging, including colour fundus photography, fluorescein angiography, optical coherence tomography, and multimodal imaging, has provided assistance in quantifying swelling, distinguishing true optic disc oedema from pseudo-optic disc oedema, and differentiating among the numerous causes of acute optic disc oedema. However, the diagnosis of disc oedema is often delayed or not made in busy emergency departments and outpatient neurology clinics. Indeed, most non-eye care providers are not able to accurately perform ocular fundus examination, increasing the risk of diagnostic errors in acute neurological settings. The implementation of non-mydriatic fundus photography and artificial intelligence technology in the diagnostic process addresses these important gaps in clinical practice.
Bio-Electrochemical Characterization of Micromachined Two- Electrode Cell Sensors

In this work, the characterization of bio-electrochemical responses from micromachined two-electrode cell sensor, which consists of a platinized working microelectrode and a micro-pseudo-reference integrated within microtitre chamber, was studied. The cyclic voltammograms of a mediator in a pL-scale volume was analyzed. The dynamic response to lactate was demonstrated for the resulting lactate amperometric bioanalytical sensors with enzyme immobilization.
The Relationship between Linguistic Features and Readability of Dini Integrated Curriculum Arabic Textbook in Government-Aided Religious School

Efforts to strengthen the Arabic language subject can further strengthen the flow of the Dini Integrated Curriculum (KBD) in Malaysia. The mastery of this subject can be measured based on the readability of students’ text. This study aims to identify the readability of the KBD Form Four Arabic textbook (al-Lughah al-Arabiah al-Muasirah) in Government Aided Religious Schools (SABKs) based on linguistic characteristics. A quantitative survey design was implemented on 694 students in five SABK zones using the proportional strata random sampling technique. The technique has passed the instrument validity and reliability tests. Data were analyzed by text, descriptive, and inferential analyses including frequency, percentage, mean, standard deviation, Kuder Richardson 20 test, and Pearson’s correlation test. The findings of the study of linguistic features show that word form dominates a high level of uniformity in the text for word category and Balagha for sentence category, while the content category is in the moderate level. The readability of the textbook is at a disappointing level. There is a strong significant relationship between verb sentences and long verb sentences with the readability of the KBD Form Four Arabic textbook. The results of the study can also be utilized by authorities to ensure the materials in Arabic textbooks can attract students to continue reading and learning more actively.
Perspectives of the Teachers on Challenges and Possibilities to Online System of Education amid COVID-19 Outbreak in Balochistan, Pakistan

The study investigates the issues of access, quality, and other major challenges to the online system of education for students in Balochistan during this pandemic of Covid-19. Using the mixed-method design, 100 participants from schools and 7 curriculum experts responded to the survey and the interview questions. Survey results suggested that majority of the schools have enough digital devices, and teachers, to some extent, have skills to use technology in teaching, but limited electricity, funds, weak internet connections, and teacher training were some of the major challenges for them. In interviews, the participants showed disappointment in terms of responsiveness of the curriculum because the textbooks have manifold deficiencies in responding to online education. Considering these deficiencies, proposals were suggested to cope with the existing situation. The findings of the study call for the need on the part of the academia, educational stakeholders, and elected representatives to start joint efforts with national and international donor agencies, technology benefactors and telecommunication operators in developing digital infrastructure to provide students with access to education, quality, and lifelong learning through various pathways. The findings can be generalized to other underdeveloped regions both within and across the country, as the public schools are confronting the same issues and the online system of education has not yet been initiated.
Using deeply time-series semantics to assess depressive symptoms based on clinical interview speech

Introduction Depression is an affective disorder that contributes to a significant global burden of disease. Measurement-Based Care (MBC) is advocated during the full course management, with symptom assessment being an important component. Rating scales are widely used as convenient and powerful assessment tool, but they are influenced by the subjectivity and consistency of the raters. The assessment of depressive symptoms is usually conducted with a clear purpose and restricted content, such as clinical interviews based on the Hamilton Depression Rating Scale (HAMD), so that the results are easy to obtain and quantify. Artificial Intelligence (AI) techniques are used due to their objective, stable and consistent performance, and are suitable for assessing depressive symptoms. Therefore, this study applied Deep Learning (DL)-based Natural Language Processing (NLP) techniques to assess depressive symptoms during clinical interviews; thus, we proposed an algorithm model, explored the feasibility of the techniques, and evaluated their performance. Methods The study included 329 patients with Major Depressive Episode. Clinical interviews based on the HAMD-17 were conducted by trained psychiatrists, whose speech was simultaneously recorded. A total of 387 audio recordings were included in the final analysis. A deeply time-series semantics model for the assessment of depressive symptoms based on multi-granularity and multi-task joint training (MGMT) is proposed. Results The performance of MGMT is acceptable for assessing depressive symptoms with an F1 score (a metric of model performance, the harmonic mean of precision and recall) of 0.719 in classifying the four-level severity of depression and an F1 score of 0.890 in identifying the presence of depressive symptoms. Disscussion This study demonstrates the feasibility of the DL and the NLP techniques applied to the clinical interview and the assessment of depressive symptoms. However, there are limitations to this study, including the lack of adequate samples, and the fact that using speech content alone to assess depressive symptoms loses the information gained through observation. A multi-dimensional model combing semantics with speech voice, facial expression, and other valuable information, as well as taking into account personalized information, is a possible direction in the future.
Viscous effects in droplet-ejecting capillary waves

Department of Physics, Emory University, Atlanta, Georgia 30322~Received 14 November 1996! Surface waves produced by parametric excitation experience a transition between simply connected wavesand droplet-ejecting waves when the applied forcing exceeds a threshold level. Our measurements on a numberof different ﬂuids indicate that low-viscosity ﬂuids have threshold accelerations which depend on only surfacetension and forcing frequency while high viscosity ﬂuids have thresholds which depend on only viscosity andforcing frequency. Models for the transition based on the condition that the wavelength, waveheight ratioapproaches a ﬁxed value at the transition are consistent with our observations. @S1063-651X~97! 05207-0#PACS number~s! : 47.20. Ma, 47.55. Dz, 68.10. 2m, 92.10. Hm
Antimicrobial resistance patterns and characterisation of emerging beta‐lactamase‐producing Escherichia coli in camels sampled from Northern Kenya

Abstract Background Animal husbandry practices in different livestock production systems and increased livestock–wildlife interactions are thought to be primary drivers of antimicrobial resistance (AMR) in Arid and Semi‐Arid Lands (ASALs). Despite a tenfold increase in the camel population within the last decade, paired with widespread use of camel products, there is a lack of comprehensive information concerning beta‐lactamase‐producing Escherichia coli (E. coli) within these production systems. Objectives Our study sought to establish an AMR profile and to identify and characterise emerging beta‐lactamase‐producing E. coli isolated from faecal samples obtained from camel herds in Northern Kenya. Methods The antimicrobial susceptibility profiles of E. coli isolates were established using the disk diffusion method, with beta‐lactamase (bla) gene PCR product sequencing performed for phylogenetic grouping and genetic diversity assessments. Results Here we show, among the recovered E. coli isolates (n = 123), the highest level of resistance was observed for cefaclor at 28.5% of isolates, followed by cefotaxime at 16.3% and ampicillin at 9.7%. Moreover, extended‐spectrum beta‐lactamase (ESBL)‐producing E. coli harbouring the bla CTX‐M‐15 or bla CTX‐M‐27 genes were detected in 3.3% of total samples, and are associated with phylogenetic groups B1, B2 and D. Multiple variants of non‐ESBL bla TEM genes were detected, the majority of which were the bla TEM‐1 and bla TEM‐116 genes. Conclusions Findings from this study shed light on the increased occurrence of ESBL‐ and non‐ESBL‐encoding gene variants in E. coli isolates with demonstrated multidrug resistant phenotypes. This study highlights the need for an expanded One Health approach to understanding AMR transmission dynamics, drivers of AMR development, and appropriate practices for antimicrobial stewardship in camel production systems within ASALs.