Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Flexible and Low-Power Wireless Smart Sensors: Reconfigurable Analog-to-Feature Conversion for Healthcare Applications

Analog-to-feature (A2F) conversion based on non-uniform wavelet sampling (NUWS) has demonstrated the ability to reduce energy consumption in wireless sensors while employed for electrocardiogram (ECG) anomaly detection. The technique involves extracting only relevant features for a given task directly from analog signals and conducting classification in the digital domain. Building on this approach, we extended the application of the proposed generic A2F converter to address a human activity recognition (HAR) task. The performed simulations include the training and evaluation of neural network (NN) classifiers built for each application. The corresponding results enabled the definition of valuable features and the hardware specifications for the ongoing complete circuit design. One of the principal elements constituting the developed converter, the integrator brought from the state-of-the-art design, was modified and simulated at the circuit level to meet our requirements. The revised value of its power consumption served to estimate the energy spent by the communication chain with the A2F converter. It consumes at least 20 and 5 times less than the chain employing the Nyquist approach in arrhythmia detection and HAR tasks, respectively. This fact highlights the potential of A2F conversion with NUWS in achieving flexible and energy-efficient sensor systems for diverse applications.
New Techniques to Measure Cliff Change from Historical Oblique Aerial Photographs and Structure-from-Motion Photogrammetry

ABSTRACT Warrick, J.A. ; Ritchie, A.C. ; Adelman, G. ; Adelman, K. , and Limber, P.W. , 2017. New techniques to measure cliff change from historical oblique aerial photographs and Structure-from-Motion photogrammetry. Oblique aerial photograph surveys are commonly used to document coastal landscapes. Here it is shown that adequate overlap may exist in these photographic records to develop topographic models with Structure-from-Motion (SfM) photogrammetric techniques. Using photographs of Fort Funston, California, from the California Coastal Records Project, imagery were combined with ground control points in a four-dimensional analysis that produced topographic point clouds of the study area's cliffs for 5 years spanning 2002 to 2010. Uncertainty was assessed by comparing point clouds with airborne LIDAR data, and these uncertainties were related to the number and spatial distribution of ground control points used in the SfM analyses. With six or more ground control points, the root mean squared errors between the SfM and LIDAR data were less than 0.30 m (minimum = 0.18 m), and the mean systematic error was less than 0.10 m. The SfM results had several benefits over traditional airborne LIDAR in that they included point coverage on vertical-to-overhanging sections of the cliff and resulted in 10–100 times greater point densities. Time series of the SfM results revealed topographic changes, including landslides, rock falls, and the erosion of landslide talus along the Fort Funston beach. Thus, it was concluded that SfM photogrammetric techniques with historical oblique photographs allow for the extraction of useful quantitative information for mapping coastal topography and measuring coastal change. The new techniques presented here are likely applicable to many photograph collections and problems in the earth sciences.
Epidemiological Data and Antimicrobial Resistance of Campylobacter spp. in Portugal from 13 Years of Surveillance

This study extensively analyzed campylobacteriosis surveillance in Portugal from 2009 to 2021, aiming to investigate demographic shifts, seasonal variations, and antimicrobial resistance (AMR) within Campylobacter isolates. Surveillance network and sentinel laboratory-based system data revealed a substantial under-notification of campylobacteriosis cases, suggesting an underestimated disease burden. Notification rates exhibited a paradigm shift, with a notable prevalence among the pediatric population, particularly in children aged 1–4 years, diverging from European reports. Additionally, an emerging trend of Campylobacter infections in younger adults (15–44 years) was observed. The study unveiled a unique seasonal distribution of cases, defying typical summer peaks seen elsewhere. AMR analysis revealed high resistance to ciprofloxacin and tetracycline, in both C. jejuni (93.7% and 79.2%, respectively) and C. coli (96.5% and 93.2%, respectively), stable throughout the studied period (2013–2021). C. coli exhibited significantly higher resistance to erythromycin, gentamicin, ampicillin and ertapenem compared to C. jejuni (p < 0.001). Multilocus Sequence Typing (MLST) data demonstrated the distribution of resistance markers across diverse sequence types, challenging the notion of a clonal origin for multidrug-resistant isolates. In conclusion, the study highlights the need for enhanced surveillance and raises concerns about alarming AMR levels, recommending the implementation of whole-genome sequencing (WGS)-based surveillance for a deeper comprehension of disease patterns and an evolving AMR landscape.
Radiometric Calibration of Landsat 5 TM Data

Landsat 5 satellite launched on March 1, 1984 has been operating well for over 23 years. Over the lifetime of Landsat 5, USGS updated its absolute radiometric calibration algorithms on May, 2003 and April, 2007, respectively in order to improve absolute calibration accuracy, consistency over time and consistency with Landsat 7 ETM+ data. Now there are much confusion on the radiometric calibration of Landsat 5 TM data which may affect the precision of the absolute calibration. In order to solve this problem, this paper analyzes the methodology on the absolute radiometric calibration of TM data and its changes in detail, to help users to carry out the radiometric calibration correctly.
SPATIAL CLUSTER AND OUTLIER IDENTIFICATION OF GEOCHEMICAL ASSOCIATION OF ELEMENTS: A CASE STUDY IN JUIRUI COPPER MINING AREA

Spatial clusters and spatial outliers play an important role in the study of the spatial distribution patterns of geochemical data. They characterize the fundamental properties of mineralization processes, the spatial distribution of mineral deposits, and ore element concentrations in mineral districts. In this study, a new method for the study of spatial distribution patterns of multivariate data is proposed based on a combination of robust Mahalanobis distance and local Moran’s I i . In order to construct the spatial matrix, the Moran's I spatial correlogram was first used to determine the range. The robust Mahalanobis distances were then computed for an association of elements. Finally, local Moran’s I i statistics was used to measure the degree of spatial association and discover the spatial distribution patterns of associations of Cu, Au, Mo, Ag, Pb, Zn, As, and Sb elements including spatial clusters and spatial outliers. Spatial patterns were analyzed at six different spatial scales (2km, 4 km, 6 km, 8 km, 10 km and 12 km) for both the raw data and Box-Cox transformed data. The results show that identified spatial cluster and spatial outlier areas using local Moran’s I i and the robust Mahalanobis accord the objective reality and have a good conformity with known deposits in the study area.
Gut Microbiome and Cancer: From Cancer Development to Therapeutics with a Special Focus on Hepatocellular Carcinoma.

The body of a human has a vast array of microorganisms termed the microbiome that impacts almost every function of the body. Gene-environment interactions play a major role in making us susceptible to cancer and the microbiome is such an environmental factor that we are exposed to from the very beginning of our lives to the very end. Increasing pieces of evidence are pointing towards an association of cancer and the microbiome. The bacteria inside our body might help us prevent some cancers as well as may increase the risk of carcinogenesis and treatment responses. Many studies are suggesting that tinkering with the microbiome might be a new way to treat and prevent many kinds of cancer. Although information on the roles of the microbiome in carcinogenesis is scant and almost no direct links have been found between these two yet. This review offers some of the recent evidences of the association between cancer and the microbiome, discuss the impact of gut bacteria on cancer and provide a detailed discussion on gut microbiota mediated therapeutic approaches with a special focus on Hepatocellular Carcinoma. The implementation of the new knowledge discovered in this subject calls for a great deal of research.
Coyote Survival and Habitat Selection in a Longleaf Pine Ecosystem.

STEVENSON, ELIZABETH ROSE. Coyote Survival and Habitat Selection in a Longleaf Pine Ecosystem. (Under the direction of Drs. Christopher E. Moorman and Christopher S. DePerno). The Coyote (Canis latrans) is a novel predator in the southeastern United States and facilitates ecologically novel interactions with other wildlife species. Though coyotes recently expanded to the southeastern United States, little data exist on vital rates of southeastern coyotes. Furthermore, knowledge of survival rates where coyotes are protected from hunting and trapping is lacking. To estimate annual survival where coyote harvest was restricted, we captured and radiocollared 31 coyotes during 2011 at Fort Bragg Military Installation, North Carolina. We used a 12-month period (Feb 2011 – Feb 2012) and knownfate modeling in Program MARK to create monthly and annual survival estimates. The model where survival varied with time (S(t)) was the most parsimonious model according to model selection results. Annual survival from February 2011 – February 2012 was 0.80 (95% CI = 0.60 – 0.91). Seven mortalities occurred during the study period, including two from vehicles, two from off-site trapping, and three from unknown causes. Though hunting and trapping were restricted, anthropogenic causes of mortality were predominant and coyote survival rates at Fort Bragg were similar to other reported estimates from the southeastern US. Fire is a disturbance that shapes plant and animal community composition around the globe, and apex predators may have cascading effects on these communities. However, scant empirical data describe how fire and predators may interact to collectively affect ecosystem processes. We examined resource selection of coyotes in a fire-maintained ecosystem to understand how fire and predators may interact to shape ecosystems. Our objective was to examine resource selection relative to fire-maintained vegetation types, years-since-fire, and manmade features that facilitate prescribed burning (i.e., roads). Coyotes selected open, grass-forb areas over forested areas when selecting a home range. Coyotes avoided areas burned 4 or more years prior but selected upland forest burned 1 and 2 years prior. Coyotes selected open areas year round, probably because of high prey availability and dense understory vegetation that provided cover. Coyote selection of more recently burned areas likely was in response to increased ability to detect prey soon after vegetation cover was reduced by fires. In ecosystems where prescribed fire is used to maintain fire-dependent plant communities, coyote resource selection may be linked to prescribed fire. Coyote habitat selection related to fire regimes may indicate an interaction with fire that could influence ecosystem function.
Understanding Cancer’s Defense against Topoisomerase-Active Drugs: A Comprehensive Review

Simple Summary Increasing number of cancer patients and significant mortality among these patients are attributed to many factors including anticancer drug resistance. Among a pool of available anticancer drugs, topoisomerase-active drugs, e.g., doxorubicin and topotecan are used by cancer patients at high dose and that leads to various side effects and post anticancer therapies complications. Therefore, efforts are warranted to understand the reasons behind such anticancer drug resistance so that better therapeutic management of cancer patients can be achieved. Such efforts could be achieved in the preclinical and clinical laboratory settings so that safer and highly efficacious anticancer drug combinations could be explored for the cancer patients. In the future, combinatorial anticancer drug approaches targeting topoisomerase enzymes can combine newer tools and technologies aided by artificial intelligence and machine learning for rapid and reliable validations of anticancer effects by combinatorial therapeutic approaches. Abstract In recent years, the emergence of cancer drug resistance has been one of the crucial tumor hallmarks that are supported by the level of genetic heterogeneity and complexities at cellular levels. Oxidative stress, immune evasion, metabolic reprogramming, overexpression of ABC transporters, and stemness are among the several key contributing molecular and cellular response mechanisms. Topo-active drugs, e.g., doxorubicin and topotecan, are clinically active and are utilized extensively against a wide variety of human tumors and often result in the development of resistance and failure to therapy. Thus, there is an urgent need for an incremental and comprehensive understanding of mechanisms of cancer drug resistance specifically in the context of topo-active drugs. This review delves into the intricate mechanistic aspects of these intracellular and extracellular topo-active drug resistance mechanisms and explores the use of potential combinatorial approaches by utilizing various topo-active drugs and inhibitors of pathways involved in drug resistance. We believe that this review will help guide basic scientists, pre-clinicians, clinicians, and policymakers toward holistic and interdisciplinary strategies that transcend resistance, renewing optimism in the ongoing battle against cancer.
RC-LAHR: Road-Side-Unit-Assisted Cloud-Based Location-Aware Hybrid Routing for Software-Defined Vehicular Ad Hoc Networks

The reliability of the communication link is quite common and challenging to handle as the topology changes frequently in vehicular ad hoc networks (VANETs). Another problem with VANETs is that the vehicles are from different manufacturers. Hence, the heterogeneity of hardware is obvious. These heterogeneity and reliability problems affect the message dissemination in VANETs. This paper aims to address these challenges by proposing a robust routing protocol capable of ensuring reliable, scalable, and heterogeneity-tolerant message dissemination in VANETs. We first introduced a hybrid hierarchical architecture based on software-defined networking (SDN) principles for VANETs, leveraging SDN’s inherent scalability and adaptability to heterogeneity. Further, a road-side unit (RSU)-assisted cloud-based location-aware hybrid routing for software-defined VANETs (SD-VANETs) that we call RC-LAHR was proposed. RC-LAHR was rigorously tested and analyzed for its performance in terms of packet delivery ratio (PDR) and end-to-end delay (EED), along with a comprehensive assessment of network traffic and load impacts on cloud infrastructure and RSUs. The routing protocol is compared with state-of-the-art protocols, Greedy Perimeter Stateless Routing (GPSR) and Opportunistic and Position-Based Routing (OPBR). The proposed routing protocol performs well as compared to GPSR and OPBR. The result shows that the EED is reduced to 20% and the PDR is increased to 30%. The network reliability is also increased up to 5% as compared to the OPBR and GPSR.
Event-Based Fixed-Time Consensus Tracking for Constrained Networked Euler–Lagrange Systems

This article delves into the challenge of fixed-time consensus tracking (FtCT) for networked Euler–Lagrange systems with customized time constraints (CTCs), especially in the presence of restricted communication and computational capabilities. In the face of intermittent and unidirectional communication scenarios, an event-based distributed fixed-time observer is designed, specifically ensuring the exclusion of Zeno phenomena in the analysis. Following this, to economize on the frequency of control input updates, an adaptive event-triggered local control approach rooted in backstepping techniques is put forward, which guarantees practical fixed-time convergence of error signals while precluding Zeno behavior. A key innovation lies in the formulation of a constrained function featuring a shift function, thereby affording a unified framework capable of flexibly addressing CTC without altering the control structure. Simulations are ultimately executed to corroborate the proposed approaches.
The Response of Vegetation Net Primary Productivity to Climate Change during 1981-2000 in the Tibetan Plateau

Based on the 0.1°×0.1° resolution map of vegetation type,soil texture and meteorological data,the atmosphere-vegetation interaction model(AVIM2) was used to simulate the response of net primary productivity(NPP) to climate change in the Tibetan Plateau.The results show that the vegetation NPP increased during the past 20 years in the Tibetan Plateau owe to the combination effects of the temperature and precipitation change.The changes of annual mean temperature and annual precipitation were positively correlated with the change of NPP during the last 20 years.The influence of precipitation change to forests and grassland NPP were higher than that of temperature,whereas the effects of precipitation to shrubs were lower than that of temperature.The total NPP for shrub and forest increased 1.14% and 0.88% per year,individually.There increasing trend reach the statistically significant level.The increasing trend for grassland NPP was gentler than that for forests and shrubs.On the whole study region,the average annual mean temperature increased 0.058 ℃ per year,annual precipitation increased and the total vegetation NPP increased during 1981—2000.
A review on human cancer and potential role of MXenes in cancer therapy

Cancer is the second leading cause of death worldwide and is having a serious impact on the global economy. Various treatment modalities are in use to treat cancer but none of the techniques is risk-free. Recently, various nanomaterials such as gold, boron, and other compounds have been investigated for radiotherapy and as anti-cancer drug carriers with promising results. MXenes are 2D novel nanomaterials and their biomedical and anticancer properties are gaining interest due to their high biomedical activity, less bio-toxicity, and photo-responsive nature. However, the biological properties of MXense have not been studied extensively, therefore, limited data is published on its in-vitro and in-vivo anticancer activities, drug loading efficacy, targeted release, and on its photothermal therapy response. In this review, we have discussed the use of nanoparticles and MXenen nanomaterial in cancer therapy. Furthermore, the role of Mxene as a photothermal agent and drug carrier has also been emphasized, along with the present challenges for the use of nanomaterials in the treatment of cancer.
Lightweight SAR Ship Detection Network Based on Transformer and Feature Enhancement

With the rapid development of synthetic aperture radar (SAR) technology, SAR remote sensing has a wide range of applications in fields, such as marine surveillance and sea rescue. Currently, the SAR ship detection model based on deep learning suffers from the problems of low detection in real time and low detection accuracy. In order to solve the abovementioned problems, this article proposes a lightweight SAR ship detection network (EGTB-Net) based on transformer and feature enhancement. First, we design a novel Ghost-ECA model as the backbone network of EGTB-Net, which reduces the number of parameters of the model and enhances the ability to identify key feature information at the same time. Then, we incorporate the transformer block in the backbone network to capture long-range dependencies, enrich contextual information, and improve the network's ability to capture different types of local information. Finally, we adopt a new SIoU loss function, which is used to solve the direction problem of mismatch between the real frame and the predicted frame and improve the network's ability to localize ship targets. The experimental results on the SAR-ship-dataset show that the mean average precision of the method is 94.83%, the detection speed is 61 frames per second, and the model size is only 5.94 M, while the model has excellent anti-interference ability.
GENETIC PROCESSES OF CAVE MINERALS IN VOLCANIC ENVIRONMENTS: AN OVERVIEW

Volcanic caves are widespread in the world and are actively explored by cavers so it is common to find descriptions of the exploration, speleogenesis and morphology of these caves in the literature. However, the accurate study of the speleothems hosted by these caves is rather new because, until recently, lava tubes and other volcanic cavities have been considered of little interest from the point of view of secondary minerals (Forti 1994). Most volcanic caves allow for the development of only a few small speleothems apart from lava stalactites and stalagmites, which normally cannot be considered as true cave formations (Hill & Forti 1997).
Rectal Sensory and Compliance Testing: A Method Comparison Study between High-Resolution Anorectal Manometry and Barostat Investigations

Abnormal visceral perception and motor function are often observed in patients with fecal incontinence, evacuation disorders and irritable bowel syndrome. The international anorectal physiology working group has proposed a standardization for anorectal function assessment, where rectal sensitivity testing is performed using an elastic balloon attached to a high-resolution anorectal manometry (HRAM) catheter. Rectal compliance, another component of rectal function evaluation, is a pressure–volume relationship that refers to the rectum’s ability to stretch and expand as it receives and holds fecal matter. There are no data available regarding the possibility of compliance testing using HRAM, although this is theoretically possible by correcting for the elastic balloon’s intrinsic properties. The gold standard for measurement of visceral sensitivity and compliance is the rectal barostat, according to the procedure described by the European COST action GENIEUR group. Data on the agreement between the two different procedures are scarce. Hence, we performed a comparative study of the HRAM and barostat investigations in 26 healthy individuals. We hypothesized that by inflating the balloon before the examination, rectal compliance can be measured with HRAM investigations, and we examined correlations and levels of agreement between the methods. Our results demonstrate that assessing rectal compliance with HRAM is technically possible; however, a strong correlation with the rectal barostat was only observed at the maximum tolerable volume (Spearman’s rho = 0.7, p = 0.02). We only found moderate correlations (Spearman’s rho = 0.562, p = 0.019) for compliance according to the barostat methodology and for rectal sensibility testing (Spearman’s rho = 0.57, p = 0.03 for maximum tolerable volume). Bland–Altman plots showed poor levels of agreement between the methods. We conclude that HRAM and the rectal barostat cannot be used interchangeably for compliance or sensitivity assessments. We suggest the development of a non-elastic balloon with a fixed size and shape to assess rectal sensory function and compliance in HRAM testing.