Miracle-dz/UniFAR-FTUs huggingface dataset:
Fabrication and Electromechanical Characterization of Silicon Nanomechanical Membrane Flexure MEMS Sensor for Gas Sensing Applications

This article reports the development and characterization of a piezoresistive silicon MEMS nanomechanical membrane-flexure (NMF) sensor and its application for the detection of hydrogen gas. The electromechanical transduction of the NMF sensor is achieved with an integrated indium tin oxide (ITO) thin film piezoresistor with a high negative gauge factor of −430. The sensors are fabricated using a standard silicon-on-insulator (SOI)-based silicon MEMS process, facilitating batch production. A novel high-resolution hybrid optical-electromechanical method was used for the strain sensing study of the NMF sensor with in situ optical surface profiling for curvature measurement through white light interferometry. The optimized sensor design showed a deflection sensitivity of 2.76 ppm[nm] $^{-{1}}$ . This work also reports the ability of the NMF sensor with signal conditioning circuit in detecting hydrogen gas in parts-per-million (ppm) concentration with good sensor response of 520 mV for 100 ppm and quick recovery using low background flow cell temperature supporting their suitability for reusable biochemical sensing applications demanding low detection limits.
Non-Contact Current Sensing System Based on the Giant Magnetoimpedance Effect of CoFeNiSiB Amorphous Ribbon Meanders

A sensitive non-contact sensing system based on the CoFeNiSiB amorphous ribbon giant magnetoimpedance (GMI) effect is proposed for current testing. The sensing system consists of a GMI probe, a sinusoidal current generator, a voltage follower, a preamplifier, a low-pass filter, and a peak detector. Four different GMI probes derived from amorphous ribbon meanders are designed and fabricated through MEMS processes. GMI probes were driven by a 10 MHz, 5 mA AC current. A permanent magnet was used to provide a bias magnetic field for the probe. The effect of the bias magnetic field on the output DC voltage was investigated. This non-contact current sensing system exhibits good sensitivity and linearity at a bias magnetic field Hbias = 15 Oe. The sensitivity can reach up to 24.2 mV/A in the ±1.5 A range.
Learning Occluded Branch Depth Maps in Forest Environments Using RGB-D Images

Covering over a third of all terrestrial land area, forests are crucial environments; as ecosystems, for farming, and for human leisure. However, they are challenging to access for environmental monitoring, for agricultural uses, and for search and rescue applications. To enter, aerial robots need to fly through dense vegetation, where foliage can be pushed aside, but occluded branches pose critical obstacles. Therefore, we propose pixel-wise depth regression of occluded branches using three different U-Net inspired architectures. Given RGB-D input of trees with partially occluded branches, the models estimate depth values of only the wooden parts of the tree. A large photorealistic simulation dataset comprising around 44 K images of nine different tree species is generated, on which the models are trained. Extensive evaluation and analysis of the models on this dataset is shown. To improve network generalization to real-world data, different data augmentation and transformation techniques are performed. The approaches are then also successfully demonstrated on real-world data of broadleaf trees from Swiss temperate forests and a tropical Masoala Rainforest. This work showcases the previously unexplored task of frame-by-frame pixel-based occluded branch depth reconstruction to facilitate robot traversal of forest environments.
Improved Modulation Bandwidth of c-Plane Micro-LED Arrays by Varying Si Doping in the Quantum Barrier

Abstract-Visible light communication (VLC) is an important complementary technology to traditional radio frequency (RF) communication due to the abundance of available frequency resources and the high data rates. VLC systems are, however, constrained by the low −3 dB bandwidth of light-emitting diodes (LED) and high bit error rates (BER). Herein, we propose a vertical-structure microLED array with an Si-doped first quantum barrier (FQB) that suppresses the quantum confinement Stark effect (QCSE), increasing the radiative recombination rate. The micro-LED array exhibits an −3 dB bandwidth of 578 MHz at 2000 A / cm2 when the Si doping content of the FQB is <inline-formula> <tex-math notation="LaTeX">$8 \times 10^{18} \mathrm{~cm}^{-3}$ </tex-math></inline-formula>. A data rate of <inline-formula> <tex-math notation="LaTeX">$1.61 \mathrm{~Gb} / \mathrm{s}$ </tex-math></inline-formula> with a BER of <inline-formula> <tex-math notation="LaTeX">$3.51 \times 10^{-3}$ </tex-math></inline-formula> over the distance of 1 m free space was demonstrated using the on-off keying (OOK) modulation scheme. This work shows great potential for high-speed VLC systems by proposing a simple way to improve communication performance.
Online anomaly detection with uncertainty estimation and concept drift adaptation using quantile regression

Deep learning algorithms played an important role in big data applications that open other opportunities to study their applicability in anomaly detection. These algorithms are used in prediction-based anomaly detection methods for detection of anomalies in time series data. Various Recurrent Neural Networks (RNN) structures particularly based on Long Short-Term Memory (LSTM) or Gated Recurrent Unit (GRU) have been reported to be used for time series anomaly detection. Despite the performance of these methods, they are affected using a fixed threshold, and the assumption of Gaussian distribution on the prediction error to identify anomalous values. In addition, these techniques do not consider uncertainty in their predictions that may lead to over-confident predictions especially when there is limited training data. This impression motivates our previous research work that proposed a new anomaly detection method called Deep Quantile Regression Anomaly Detection (DQR-AD) that used confidence interval to identify anomalies in time series. However, the speed at which the time series data arrives and the dynamic change of normal behavior in a non-stationary environment will affect the offline training of DQR-AD using historical data. To mitigate these problems, this paper proposed an online DQR-AD that will enable the adaptation of concept changes in the data. Experiments conducted indicate that online DQR-AD method has better performance than its counterpart methods with relatively 10% margin. This result demonstrates how concept drift adaptation strategies adopted in the proposed method improve the performance of anomaly detection in time series.
Modelo estrátegico de aprendizaje organizacional para impulsar la competitividad municipal

This research was conducted to identify elements of organizational learning related to municipal competitiveness; presents the conceptual foundations and empirical research results in the municipalities in the region Toluca, State of Mexico It is a mixed exploratory study through a survey, obtained correlation coefficients to contrast the assumptions of scholars about these issues with the results of field research. The main result is a model that includes six factors of organizational learning arises: environment; experience; innovation; information and communication technologies; information and knowledge. The findings highlight that despite the model presented is applicable in any field, in the municipal actions and strategies to put into practice involving municipal authorities, civil servants, businessmen and the general public are needed.
The impact of meteorological persistence on the distribution and extremes of ozone

CASTNET (Clean Air Status and Trends Network) ozone and temperature data and large‐scale meteorological analysis are used to quantify the extent to which meteorological events and their persistence impact ozone with an emphasis on the high end of the ozone distribution (greater than the 90th percentile). Ozone increases with each successive stagnation day in all regions of the U.S., with the highest increase in the Northeastern U.S. (0.4 standard deviation or ∼4.7 ppb per successive stagnation day). Ozone increases with days since cyclone passage only in the Northeastern and Mid‐Atlantic regions of the U.S., but on average not enough to reach the 90th percentile concentration. Persistent high temperature does not result in further ozone increases in any region. On the interannual timescale there is little evidence that summers with large numbers of the above events increase ozone preferentially on the high end of the ozone distribution.
Smart Street Lighting Control System Using PWM

The goal of the IoT-based smart street light system is to conserve energy by decreasing manual labour requirements and electricity waste. The energy that is conserved can be put to a variety of uses, including domestic and commercial ones. An LDR sensor is used in the system to control how the street lights are turned on and off in response to the amount of ambient light. This sensor's output is a relay, and it simply detects light and dark. Through the internet, anyone may get up-to-date information about the condition of the street lights, assuring great dependability and long-term stability. The amount of light is adjusted throughout the day using a programmable board. In comparison to the current system, the proposed system performs better.
Systematic Review of Post-Traumatic Parkinsonism, an Emerging Parkinsonian Disorder Among Survivors of Traumatic Brain Injury

This systematic review focuses on an increasing subset of traumatic brain injury (TBI) survivors who develop post-traumatic parkinsonism (PTP), characterized by slowness of movement (bradykinesia), rigidity (stiffness), postural instability, and resting tremors caused by obstruction or damage to deep brain structures of the basal ganglia. PTP is rare, and one hypothesis to explain PTP rarity is that TBIs severe enough to affect deep brain structures are often lethal; however, with increasing survivability of TBIs, these numbers are expected to increase. The goal of this review is to raise awareness of an expected global increase of a subgroup of TBI patients who are treatment responsive and report therapeutic results aiding providers in diagnosing, educating, and treating PTP patients. Literature over the past 100 years was considered, and 44,663 peer-reviewed articles were identified. Inclusion criteria required a clinical indication of parkinsonian signs and TBI. Twenty-six case reports were ultimately included from which 36 individual patient data points were extracted for this review. Between 1980 and 2010, there has been an increase in reporting of PTP decade after decade. Forty-seven percent of PTP cases have 1–6 months of latency to symptom onset, and 83% of cases were male. PTP can occur with or without presence of brain lesions, and the most common type of injuries that cause PTP are motor vehicle accidents followed by falls. PTP patients are responsive to surgery or medication treatments. Further detail on PTP symptomology, treatment responsiveness, and injury types is provided.
Smoke Detection Based on Wavelet Forest Background Model

In this paper, a fast wavelet based background modeling is introduced, which need only a few image sequences. The building of our background modeling mainly concludes four steps. The first step is getting the first-layer wavelet coefficients from background image. Secondly, separate the three high-frequency region into several 2*2 blocks, and calculate the mean and difference of every block. Then, connect and label the blocks with similar mean and difference, and re-calculate then mean and difference with same label. At last, combined the pixels information of wavelet low-frequency with its corresponding positions the eigenvector matrix of background is constructed. In addition, after iterative training, it can also be applied to fixed camera scenes.
Deciphering the origin and therapeutic targets of cancer of unknown primary: a case report that illustrates the power of integrative whole-exome and transcriptome sequencing analysis

Cancer of unknown primary (CUP) represents a significant diagnostic and therapeutic challenge, being the third to fourth leading cause of cancer death, despite advances in diagnostic tools. This article presents a successful approach using a novel genomic analysis in the evaluation and treatment of a CUP patient, leveraging whole-exome sequencing (WES) and RNA sequencing (RNA-seq). The patient, with a history of multiple primary tumors including urothelial cancer, exhibited a history of rapid progression on empirical chemotherapy. The application of our approach identified a molecular target, characterized the tumor expression profile and the tumor microenvironment, and analyzed the origin of the tumor, leading to a tailored treatment. This resulted in a substantial radiological response across all metastatic sites and the predicted primary site of the tumor. We argue that a comprehensive genomic and molecular profiling approach, like the BostonGene© Tumor Portrait, can provide a more definitive, personalized treatment strategy, overcoming the limitations of current predictive assays. This approach offers a potential solution to an unmet clinical need for a standardized approach in identifying the tumor origin for the effective management of CUP.
Cosmogenic 26Al/10Be surface production ratio in Greenland

The assumed value for the cosmogenic 26Al/10Be surface production rate ratio in quartz is an important parameter for studies investigating the burial or subaerial erosion of long‐lived surfaces and sediments. Recent models and data suggest that the production ratio is spatially variable and may be greater than originally thought. Here we present measured 26Al/10Be ratios for 24 continuously exposed bedrock and boulder surfaces spanning ~61–77°N in Greenland. Empirical measurements, such as ours, include nuclides produced predominately by neutron‐induced spallation with percent‐level contributions by muon interactions. The slope of a York regression line fit to our data is 7.3 ± 0.3 (1σ), suggesting that the 26Al/10Be surface production ratio exceeds the commonly used value of 6.75, at least in the Arctic. A higher 26Al/10Be production ratio has implications for multinuclide cosmogenic isotope studies because it results in greater modeled burial durations and erosion rates.
Swine Gastrointestinal Microbiota and the Effects of Dietary Amino Acids on Its Composition and Metabolism

Many researchers consider gut microbiota (trillions of microorganisms) an endogenous organ of its animal host, which confers a vast genetic diversity in providing the host with essential biological functions. Particularly, the gut microbiota regulates not only gut tissue structure but also gut health and gut functionality. This paper first summarized those common bacterial species (dominated by the Firmicutes, Bacteroidota, and Proteobacteria phyla) in swine gut and then briefly discussed their roles in swine nutrition and health, which include roles in nutrient metabolism, pathogen exclusion, and immunity modulation. Secondly, the current knowledge on how dietary nutrients and feed additives affect the gut bacterial composition and nutrient metabolism in pigs was discussed. Finally, how dietary amino acids affect the relative abundances and metabolism of bacteria in the swine gut was reviewed. Tryptophan supplementation promotes the growth of beneficial bacteria and suppresses pathogens, while arginine metabolism affects nitrogen recycling, impacting gut immune response and health. Glutamate and glutamine supplementations elevate the levels of beneficial bacteria and mitigate pathogenic ones. It was concluded that nutritional strategies to manipulate gut microbial ecosystems are useful measures to optimize gut health and gut functions. For example, providing pigs with nutrients that promote the growth of Lactobacillus and Bifidobacterium can lead to better gut health and growth performance, especially when dietary protein is limited. Further research to establish the mechanistic cause-and-effect relationships between amino acids and the dynamics of gut microbiota will allow swine producers to reap the greatest return on their feed investment.
Impact of Plasmodium relictum Infection on the Colonization Resistance of Bird Gut Microbiota: A Preliminary Study

Avian malaria infection has been known to affect host microbiota, but the impact of Plasmodium infection on the colonization resistance in bird gut microbiota remains unexplored. This study investigated the dynamics of Plasmodium relictum infection in canaries, aiming to explore the hypothesis that microbiota modulation by P. relictum would reduce colonization resistance. Canaries were infected with P. relictum, while a control group was maintained. The results revealed the presence of P. relictum in the blood of all infected canaries. Analysis of the host microbiota showed no significant differences in alpha diversity metrics between infected and control groups. However, significant differences in beta diversity indicated alterations in the microbial taxa composition of infected birds. Differential abundance analysis identified specific taxa with varying prevalence between infected and control groups at different time points. Network analysis demonstrated a decrease in correlations and revealed that P. relictum infection compromised the bird microbiota’s ability to resist the removal of taxa but did not affect network robustness with the addition of new nodes. These findings suggest that P. relictum infection reduces gut microbiota stability and has an impact on colonization resistance. Understanding these interactions is crucial for developing strategies to enhance colonization resistance and maintain host health in the face of parasitic infections.
Mosquito species encountered in a flooded grassland dambo in Kenya

Etude des larves et pupes de moustiques recoltees dans une prairie inondable de la province centrale du Kenya, pendant la courte saison des pluies. Aedes cumminsii mediopunctatus, Ae. lineatopennis et Ae. sudanensis sont collectes pendant 8, 9 et 18 jours respectivement, puis disparaissent apres une generation
The temperature‐ballast hypothesis explains carbon export efficiency observations in the Southern Ocean

Carbon export from the Southern Ocean exerts a strong control on the ocean carbon sink, yet recent observations from the region demonstrate poorly understood relationships in which carbon export efficiency is weakly related to temperature. These observations conflict with traditional theory where export efficiency increases in colder waters. A recently proposed “temperature‐ballast hypothesis” suggests an explanatory mechanism where the effect of temperature‐dependent respiration is masked by variation in particle‐ballast as upwelling waters move northward from Antarctica. We use observations and statistical models to test this mechanism and find positive support for the hypothesized temperature‐ballast interactions. Best fitting models indicate a significant relation between export efficiency and silica‐ballast while simultaneously revealing the expected inverse effect of temperature once ballast is accounted for. These findings reconcile model predictions, metabolic theory, and carbon export observations in the Southern Ocean and have consequences for how the ocean carbon sink responds to climate change.
Hydrocarbon measurements at Pabstthum during the BERLIOZ campaign and modeling of free radicals

[1] The Photochemistry Experiment in BERLIOZ (PHOEBE) was conducted in July/August 1998 at a rural site located near the small village Pabstthum, about 50 km NW of downtown Berlin. More than 60 nonmethane hydrocarbons (NMHC) in the range of C2–C10 were measured using two in situ gas chromatography (GC) systems. The first (GC1) was capable of measuring C2–C10 hydrocarbons with a relatively high separation efficiency but low time resolution (80–90 min), while GC2 provided quasi-continuous measurements of C5–C10 hydrocarbons with a time resolution of 20 min but with a poorer separation efficiency than GC1. The advantages of both systems were joined by interpolation between two data points of GC1 with the pattern given by GC2. For compounds that could not be reliably measured with GC2, patterns of compounds with similar reactivity were used. Air masses with the lowest photochemical age as estimated from the toluene/benzene ratio and the highest hydrocarbon mixing ratios were observed on 20 and 21 July when air was advected from the direction of Berlin. Alkanes were the most abundant hydrocarbons (∼60%) on a molecular basis, followed by alkenes and aromatics. The reactivity of the hydrocarbons toward OH was dominated by the alkenes (>60%), with isoprene and α-pinene constituting the major part. The hydrocarbon data were used together with the other trace gases measured at Pabstthum to simulate OH, HO2, and RO2 concentrations with the condensed chemical box model RACM. Relatively good agreement of the simulated radical concentrations with the spectroscopic measurements made at Pabstthum is observed for NOx mixing ratios >5 ppb, whereas the model overestimates OH and HO2 by 100% and 40%, respectively, at low NOx. The discrepancy between measured and modeled OH does not correlate with the concentration of particles. The RO2 concentrations are in good agreement with the measurements over the entire range of NOx. Sensitivity studies show that peroxyacetyl nitrate (PAN) is an important radical source and that missing volatile organic compound (VOC) reactivity is an unlikely explanation for the overestimation of HOx: By doubling of the VOC reactivity, OH and HO2 can be brought into agreement. However, the model then overestimates the organic RO2 concentrations by almost a factor of 2. Another important finding is that RACM overestimates the measured NO/NO2 ratio by 25%. This and the overestimation of HO2 lead to an overprediction of the local ozone formation rate by about 40% at low NOx mixing ratios.
Midwives as Adult Educators: An investigation of midwives’ perceptions about the educational dimension of their profession

This article deals with the educational dimension of Midwifery, as manifested in the context of perinatal education programmes in Greece. Despite the internationally recognized value of childbirth education in reducing perinatal mortality and morbidity, and despite the rich activity of midwives in terms of perinatal education, their role as adult educators has received limited scientific attention and support. The purpose of this study is to investigate whether and to what extent midwives teaching in perinatal programmes perceive their role as educators, as well as whether and in what way they are prepared for this role. It also investigates whether and what form of training midwives receive to their role in perinatal education. The study followed the specifications of qualitative design and data was collected through in-depth semi-structured interviews with twelve (12) midwives - trainers in perinatal education, as well as with eight (8) women and men who have participated in childbirth classes in Greece. The findings highlight the need to further support midwives in their educational role and to enhance their educational practice by integrating the principles of Adult Education.