Miracle-dz/UniFAR-FTUs huggingface dataset:
Stronger selective constraints on the mitochondrial genome in flying fishes

Flying fishes, which use their wing-like pectoral fins and hypocercal caudal fin to glide through the air to avoid underwater predators, have independently evolved flight behavior, making them ideal for the study of adaptive evolution. To investigate the adaptation of flight behavior in flying fishes and the origin of Beloniformes fishes, this study obtained the complete mitochondrial genomes of Cheilopogon nigricans and Oxyporhamphus micropterus and constructed the DNA sequences extracted from these newly sequenced mitochondrial genomes with the DNA sequences of 32 previously published mitochondrial genomes into a dataset for reconstructing the phylogenetic relationships of Beloniformes fishes. The phylogeny that emerged strongly supported the possibility that flying fishes developed from halfbeaks and the progressive transition of flying fishes from two-wing to four-wing gliding. The divergence time analysis showed that the split between the suborder Belonidei and the family Adrianichthyidae occurred roughly 77.08 Mya, which fell within the period of evolution of the Indian plate in the late Cretaceous. Selection analyses revealed that flying fishes have a lower dN/dS ratio than the other members of Beloniformes, indicating that flying fishes experienced stronger purifying selection to eliminate deleterious mutations to maintain efficient energy metabolism to adapt to flight behavior. Moreover, this work found the positively selected signal in the ND4 gene, suggesting that different mitogenomic genes might have undergone different selective patterns during adaptive evolution.
Combining energy-based focal ablation and immune checkpoint inhibitors: preclinical research and clinical trials

Energy-based focal therapy (FT) uses targeted, minimally invasive procedures to destroy tumors while preserving normal tissue and function. There is strong emerging interest in understanding how systemic immunity against the tumor can occur with cancer immunotherapy, most notably immune checkpoint inhibitors (ICI). The motivation for combining FT and ICI in cancer management relies on the synergy between the two different therapies: FT complements ICI by reducing tumor burden, increasing objective response rate, and reducing side effects of ICI; ICI supplements FT by reducing local recurrence, controlling distal metastases, and providing long-term protection. This combinatorial strategy has shown promising results in preclinical study (since 2004) and the clinical trials (since 2011). Understanding the synergy calls for understanding the physics and biology behind the two different therapies with distinctive mechanisms of action. In this review, we introduce different types of energy-based FT by covering the biophysics of tissue-energy interaction and present the immunomodulatory properties of FT. We discuss the basis of cancer immunotherapy with the emphasis on ICI. We examine the approaches researchers have been using and the results from both preclinical models and clinical trials from our exhaustive literature research. Finally, the challenges of the combinatory strategy and opportunities of future research is discussed extensively.
The Evaluation of the Accuracy of Survey Results: Some Canadian Experiences

Summary The paper summarizes the four objectives of survey evaluation programme: to measure the accuracy of survey results in order to guide users; to analyse sources of error with a view to subsequent improvement; to evaluate alternative methods of survey design; to institute, in the case of a regular, periodic survey, a continuing control procedure. Much of the paper is devoted to the summarization of concrete Canadian experiences with respect to the evaluation of different specific sources of error: sampling errors, coverage errors, response errors, non-response errors, processing errors.
A PID controller based on the processor utilization artifact within a real-time multitask control system

Codesign of control and scheduling systems is commonly used in the literature to address scheduling artifacts such as latencies and jitters. However, As controllers’ designs remain unchanged and fail to express any concerns regarding this matter, it becomes challenging to quantify the quality of control and its trade-off with resource utilization while adapting control or scheduling settings at runtime. In the present article, we propose a new proportional–integral–derivative (PID) controller design for the problem of scheduling artifacts. Based on our prior work, the latency processor utilization is revealed as a hidden artifact for the control deterioration when developing new predicted PID controller terms. This artifact effect is proven analytically using a codesign task model and considering an extrapolated measurement. The effectiveness of the proposed solution is assessed with a benchmark system and compared with previous works.
On theMeasurement ofCurvature ina Quantized Environment

Some aspects oftheapplication ofthemathematical concept ofcurvature as a practical descriptor ofshapeforpattern recognition andimageprocessing applications are investigated. Theaccuracytowhichthecurvature oftheboundary ofa binary (silhouette) shapecan be estimated froma givenquantized version ofthatshapedepends upon twofactors intheestimation process:thecontour-tracing algorithm bywhichboundary points on thequantized shape are defined andthemethodwhereby the curvature function estimate issmoothed topartially remove the quantization noiseresulting fromthedigitization oftheoriginal shape. Inthis paper,sixcontour-tracing algorithms aredescribed and usedtoextract curvature functions fromquantized testshapes in theabsence ofsmoothing ofanykind.Modelsoftheaveragequan- tization noise characteristics inthefrequency domain arethende- veloped forthecurvature functions corresponding toeachofthe sixcontour-tracing algorithms. Themodels areusedtocomparethe performance ofthesixalgorithms on thebasisofthequantization noise characteristics ofeach. Itisfoundthattheuseful bandwidth ofcurvature functions obtained fromquantized shapes issomewhat less thanthetheoretical limit imposed bytheNyquist sampling theorem. Themodelsde- veloped servetodemonstrate thevariation intheuseful bandwidth ofthecurvature functions corresponding toeachcontour-tracing algorithm. Thevariation inbandwidth withquantizing arrayresolu- tion canalso bepredicted withthemodels. Therelationship between thebandwidth ofa curvature function andtheamountofdetail representable inthecorresponding curveintheplane isthenex- plored. Finally, some characteristics oftheprocessofsmoothing curvature functions toeliminate quantization noise arepresented. IndexTerms-Contour coding, contour tracing, curvature, image processing, patterm recognition, quantization noise, two-dimensional.
The entity and event recognition method of power dispatching text information based on BERT-CRF

In order to improve the accuracy of power dispatching text analysis and the ability to guide the operation of the power grid, a power dispatch text entity recognition method is proposed based on Bidirectional Encoder Representations from Transformers-Conditional Random Field (BERT-CRF). Taking the power grid fault handling plan text as the research object, the entity marking method of the fault handling plan is proposed. The word vector of the plan entity is calculated based on the BERT pre-training model, the characterization ability of the professional entity of the plan is enhanced by fine-tuning the initial BERT parameters, and the recognition ability of the plan text sequence is improved from the overall situation to access the CRF layer in the neural network. Thus, an entity recognition model of fault handling plan is established based on the BERT-CRF. Through the verification of a power grid fault handling plan, the proposed method has higher power dispatch entity and event recognition accuracy compared with other algorithms.
Simulated Rupture Dynamics and Radiated Energy on Heterogeneously Damaged Faults

Rupture dynamics along a heterogeneous fault is studied in the framework of the recently developed damage‐breakage rheological model. The model utilizes a fault structure accommodating shear and wear in a heterogeneous weak fault‐core a few centimeters thick, separating two blocks with damage level gradually decreasing toward the host rock. We first demonstrate the similarity of the static stress field around a fault, represented by a three‐body tribosystem, to the one developed around a rough frictional interface. We show that both models predict heterogeneous stress field pattern. We then apply simulations of rupture on heterogeneously damaged faults. We show that increasing initial heterogeneity amplitudes is associated with smaller events with lower slip rates. The simulations further allow us to quantify the amount of accumulated damage correlative with wearing. During the propagating rupture, the strength of the fault‐core evolves, leading to higher wear generation along relatively strong zones or barriers. The total wear production in a given event is strongly dominated by the initial damage heterogeneity. Processing of synthetic seismograms shows excess energy radiation of high‐frequency seismic waves comparing to the expected radiation from planar faults. This radiation is enhanced with the increase in the variability of fault strength heterogeneity. Further calculations of the scaled energy show good fit with previous seismological and laboratory observations and demonstrate the impact of fault heterogeneity on radiated energy during dynamic rupture. Therefore, initial fault heterogeneity, manifested by fault‐core strength or by geometrical irregularity controls many aspects of earthquake rupture, including slip displacement and velocity.
Retinal motion statistics during natural locomotion

Walking through an environment generates retinal motion, which humans rely on to perform a variety of visual tasks. Retinal motion patterns are determined by an interconnected set of factors, including gaze location, gaze stabilization, the structure of the environment, and the walker’s goals. The characteristics of these motion signals have important consequences for neural organization and behavior. However, to date, there are no empirical in situ measurements of how combined eye and body movements interact with real 3D environments to shape the statistics of retinal motion signals. Here, we collect measurements of the eyes, the body, and the 3D environment during locomotion. We describe properties of the resulting retinal motion patterns. We explain how these patterns are shaped by gaze location in the world, as well as by behavior, and how they may provide a template for the way motion sensitivity and receptive field properties vary across the visual field.
Control of infinite-dimensional plants

In sliding mode control theory the major attention has been paid to finite dimensional systems described by ordinary differential equations. However, mathematical models of a wide range of processes in modern technology are partial differential equations, integro-differential equations and equations with delays. Attempts at theoretical generalisations and applications of sliding modes to control of infinite-dimensional plants show that control scientists and engineers are faced the challenge of increased complexity. Practically all the concepts of discontinuous control theory should be completely revised. Even the basic concepts discontinuity surface, sliding mode, component-wise design should be clarified or reintroduced. In the examples in this chapter we have touched upon infinite-dimensional systems mainly with distributed control.
Accounting for natural and extraneous variation in the analysis of field experiments

We identify three major components of spatial variation in plot errors from field experiments and extend the two-dimensional spatial procedures of Cullis and Gleeson (1991) to account for them. The components are nonstationary, large-scale (global) variation across the field, stationary variation within the trial (natural variation or local trend), and extraneous variation that is often induced by experimental procedures and is predominantly aligned with rows and columns. We present a strategy for identifying a model for the plot errors that uses a trellis plot of residuals, a perspective plot of the sample variogram and, where possible, likelihood ratio tests to identify which components are present. We demonstrate the strategy using two illustrative examples. We conclude that although there is no one model that adequately fits all field experiments, the separable autoregressive model is dominant. However, there is often additional identifiable variation present.
Natural gas station flame detection based on YOLO v5 target detection algorithm

Fire is a great danger to the society and economy as well as human life safety, and a small spark can lead to a serious fire. In order to improve the reliability of natural gas station fires warning system, this paper employ YOLO v5 target detection algorithm to investigate the detection of station flames. Firstly, 5488 official datasets and flame images searched for the Internet are collected as training sets and labeled. Secondly, the labeled images are used to train the YOLOv5 network model under Linux operating platform to get the appropriate weighting coefficients to minimize the value of the model loss function. Finally, the trained model is used to identify and detect the flames in the actual natural gas station site environment. The experimental results found that the YOLOv5 algorithm model can achieve real-time supervision of flames, with recognition average precision up to 89.2, fast flame detection and high recognition sensitivity. This work helps to facilitate the realization of real-time monitoring of flames and other hazardous factors of natural gas stations and improve station safety.
The Intriguing Life of Massive Galaxies: The Connections between αs, β and Merging

Abstract In this proceeding paper, we discuss the important underlying connections between the faint end slope αs of the stellar mass function of star-forming galaxies, the logarithmic slope β of the sSFR-mass relation and merging through the continuity approach, as we introduced in Peng et al. (2010, hereafter P10) and (2012, hereafter P12).
Improved Particle Swarm Optimization Algorithm for Multi-Objective Optimization

Particle swarm optimization(PSO) algorithm is an important measure for solving multi-objective(MO) problems.The diversity and practicability of Pareto optimal solution set are not good when using common PSO to MO problems.In view of this problem,an improved PSO algorithm is advanced.In the improved PSO,individual elitism set is advanced which is good for the choice of more individual optimal position.At the same time,the variancebetween objective function values is considered when the individual fitness is evaluated.If the variance is bigger,the individual fitness is also bigger.So the optimal solutions with big variance from objective functionvalues are avoided.Simulation results from three classical test functions show that the diversity and practicability of the optimal solution set are better by using the improved PSO than using common PSO.So,the improved measure is valid.
Numerical Investigation of SRB Ignition Overpressure

The numerical simulation of SRB ignition overpressure was performed to clarify the mechanism of ignition overpressure (IOP) under the same conditions as a solid rocket booster (SRB) of the Space Shuttle Columbia for the STS-1 mission. Two governing equations: 1) the Euler equations and 2) the linearized Euler equations (LEE) are employed to capture pressure fluctuations without attenuating their amplitudes as much as possible. It is assumed that gas is calorically perfect and that combustion gas, whose specific heat ratio is 1.18, fills the overall computational region. Computations are carried out for the axisymmetric case, where the ground is horizontal, and for the three-dimensional case, where the ground is eiter horizontal or oblique. The time history of pressure fluctuation shows reasonable agreement with the measured data on the SRB for the STS-1 mission. Moreover, the detailed mechanism of IOP was made clear, and the merit of using an oblique wall in a launch pad was assured to reduce the effect of overpressure waves on the body of spacecraft.
Internationalisation and English medium education in Vietnamese universities: Professional role transformation among English language lecturers

This paper investigates an emerging professional role transformation in Vietnamese universities, whereby English language teaching (ELT) lecturers transform themselves into English medium instruction (EMI) lecturers in a discipline new to them. Through interviews with five ELT/EMI lecturers working in separate universities and different disciplines, the study investigates reasons for their decision to engage in such professional mobility, their role transformation experience, and its implications for educational quality. We argue that participants’ move into EMI was shaped by the strategic imperative for higher education internationalisation, and the mistaken belief that EMI alone can achieve the English language development students require for academic success. It is also argued that the transformation option made available to the participants was not the best use of their skills, and that a profound change of perspective is needed at the institutional level to most effectively use the strengths of ELT lecturers to support educational quality.
The Incidence and Severity of Patient-Reported Side Effects of Chemotherapy in Routine Clinical Care: A Prospective Observational Study

Introduction: Understanding patients' self-reported chemotherapy side effects is significant because it affects patients' quality of life (QOL) and compliance with treatment. Our current knowledge of chemotherapy side effects comes from available literature, whose external validity is questionable. Moreover, there are very few studies available in the literature that focus on various cancers and their associated side effects. Methods: A single-center, prospective observational study was conducted at a tertiary care center from July 2019 to July 2021. After deriving the sample size, we interviewed 76 consecutive study patients with gastric, periampullary, colorectal, and breast cancer for six months after chemotherapy initiation with a structured patient-reported outcome tool adapted in English and Tamil to record the side effects like diarrhea, vomiting, chest pain, constipation, dyspnea, fatigue, mucositis, and rash. The grading of symptoms was done according to the Common Terminology Criteria for Adverse Events version 5.0. The frequency and prevalence of side effects were calculated as the number of patients who reported the side effect of any grade at least once during the follow-up period. The incidence rate of side effects was calculated in terms of person-time. The association between each side effect and cancer type was calculated using the chi-square test and Fisher's exact test as appropriate. Results: Of the 77 patients in the study, 51.9% were male, 63.6% were between 40 and 60 years of age, 45.5% had stage-3 disease, and 44.2% received neoadjuvant treatment. During the six-month follow-up period, 97.4% of patients experienced at least one side effect. Fatigue was the most common side effect (87%), followed by loss of appetite (71.4%) and diarrhea (49.4%). Approximately 66.7% of patients experienced six or more side effects. There was a statistically significant difference in the frequency of side effects between cancer types. However, age, socioeconomic status, BMI, comorbidity, chemo-intent, and stage of disease did not affect the frequency of side effects. Conclusions: This study highlights the need to integrate patient-reported side effects into routine clinical practice. Identifying these side effects, even if they are mild in intensity, and managing them in a timely manner may improve the patient's emotional state, QOL, and compliance with chemotherapy.
A novel PCB fault diagnosis method based on tiny object detection

With the rapid development of science and technology and the advent of the information age, the number of components used in electronic devices has increased sharply, making its internal circuit structure increasingly complex. Printed Circuit Boards (PCBs), as part of electronic devices, are becoming smaller and more integrated, resulting in a much greater increase in the probability of failure and the difficulty of detection. Therefore, to reduce the difficulty and cost of PCB fault diagnosis, it is very necessary to explore and study new PCB diagnosis methods. This paper first reconstructs the PCB dataset by ESRGAN, and then the CenterNet based on the center point is introduced and improved. The ResNeSt based on the segmentation attention mechanism is integrated with CenterNet to realize the PCBs fault diagnosis method based on the tiny object detection method. Experiments have proved that the method can achieve 99.42% mAP.
Pinhkngyan: paths taken to recognizing, doing and developing Indigenous methodologies

It is agreed that Indigenous scholars should be central in researching Indigenous issues. However, the literature on Indigenous research methodologies remains vague on who should be involved. This study aims to lower the entry barrier to Indigenous methodologies for anyone wholeheartedly committed to contribute to the decolonizing processes of Indigenous communities and beyond. We do so by exploring the main challenges experienced by the first author during her doctoral journey and highlighting how these challenges were dealt with. Four themes identified were as follows: (1) the colonial gaze, (2) battling with the concept of authenticity, (3) recognizing Indigeneity in the ordinary, and (4) reconciliation with the past to pave the way toward a better future. Three lessons learned are discussed. A vision for a more inclusive Indigenous inquiry is offered, suggesting that reconnection, reclaiming and sovereignty are key to establishing an ethical space between Indigenous ways of knowing and the existing dominant knowledge systems.
A dropout-resilient verifiable privacy-preserving federated learning

Federated learning enables multiple parties to jointly train a global model without sharing the original data, which has attracted much attention. Existing research work shows that even sharing local gradients will leak local data. What's worse, the server may deliberately tamper with the aggregation results, resulting in user privacy leakage or other attacks, so users need to verify the correctness of the calculation results returned by the server. In this paper, we design a verifiable privacy-preserving scheme where the server is honest and curious but has the additional ability to forge the aggregated results. The proposed scheme can guarantee the privacy gradient of honest users under the condition that no more than t users collude with the server. During the execution of the protocol, the user is allowed to drop out at any phase, and the aggregated results is kept secret from the server. In addition, each user can verify the correctness of the server’s calculation results, which is the ciphertext of the aggregated results.