Miracle-dz/UniFAR-FTUs huggingface dataset:
Obstacle Recognition and Avoidance for UAVs Under Resource-Constrained Environments

Existing resource-intensive obstacle avoidance techniques are hard to be applied on the small-size Unmanned Aerial Vehicles (UAVs) that have limited sensing and computation capacity. Therefore, it is necessary to develop an obstacle recognition and avoidance scheme which works under resource-constrained environments. To this backdrop, this paper first presents an obstacle recognition model based on monocular vision feature points. Afterwards, an obstacle recognition algorithm is put forward, whose computational complexity is low. Then, an obstacle avoidance method is proposed to regulate the obstacle-avoidance path of a UAV until it arrives its destination. To evaluate the effectiveness of the presented algorithms, we design and implement a simulation platform on Objective Modular Network Testbed in C++ (OMNeT++), and conduct a series of experiments. Experimental results show that the proposed model and algorithms can effectively guide a micro UAV to its destination using only an embedded processor and 0.5kg extra load. Even in poor communication conditions, the UAV can independently avoid obstacles and reach the destination only by acquiring the destination coordinates from the ground station.
An Empirical Study of Impact Factors on the Alignment of Cloud Computing and Enterprise

In the era of big data, where cloud computing proves to be an essential technology, its ability to align itself with enterprise is the key to facilitate business process reengineering and innovation and enhance enterprise value. In order to identify the key factors influencing the alignment of cloud computing and enterprises in Zhongguancun Technology Park, this paper, based on the dynamic capability theory and taking into account the ever-changing business environment in the Zhongguancun Technology Park, focused on three factors of an enterprise, namely Enterprise Dynamic Capability, Organization Flexibility and IT Flexibility, and built a theoretical model to study how these three factors influence the alignment of cloud computing. The paper measured the impact by two dimensions, Alignment Depth and Alignment Breadth. The results were tested by data collected in questionnaires and the Structural Equation Model (SEM) empirically. The findings showed that enterprise dynamic capability and IT flexibility both have a positive impact on the alignment depth and alignment breadth of cloud computing.
Investigations of an Original Small Power Induction Heater

An original construction of an induction heater was presented in the paper. The device is equipped with a control system for feedstock temperature. In order to obtain a sufficient value of electromagnetic field in the work area, a current resonance phenomenon was used. The maximum power of the inductor was assumed to be 2 kW, which allows to heat a steel pipe of 20 mm diameter and 3 mm wall thickness up to 100°C. An original system allowing automatic adjustment of the temperature was developed. The algorithm allows to autonomously adjust the resonance frequency, which is depending on the material of the feedstock. In order to control the feedstock temperature a discrete PID controller was implemented. Measurements were carried out for a cylindrical inductor and for a resonance frequency of approx. 71 kHz.
A study on predicting and diagnosing non-communicable diseases: case of cardiovascular diseases

Heart disease causes millions of deaths worldwide. Many approaches have been proposed for the prediction of heart disease. Several machine learning, deep learning, and data mining algorithms are used in the detection and diagnosis of heart disease based on parameters or risk factors. The most used algorithms are Naïve Bayes, Machine Vector Support, decision tree, KNNs, and artificial neural networks. The most frequently used parameters or risk factors are the 14 attributes of the UCI Cleveland standard. In this article, a study on these different approaches is carried out. This study shows diversity in relation to the choices and the use of different attributes in the prediction of cardiovascular diseases.
Propensity for Risk in Reproductive Strategy Affects Susceptibility to Anthropogenic Disturbance

Animals initiate, interrupt, or invest resources in reproduction in light of their physiology and the environment. The energetic risks entailed in an individual’s reproductive strategy can influence the ability to cope with additional stressors, such as anthropogenic climate change and disturbance. To explore the trade-offs between internal state, external resource availability, and reproduction, we applied state-dependent life-history theory (SDLHT) to a dynamic energy budget (DEB) model for long-finned pilot whales (Globicephala melas). We investigated the reproductive strategies emerging from the interplay between fitness maximization and propensity to take energetic risks, as well as the resulting susceptibility of individual vital rates to disturbance. Without disturbance, facultative reproductive behavior from SDLHT and fixed rules in the DEB model led to comparable individual fitness. However, under disturbance, the reproductive strategies emerging from SDLHT increased vulnerability to energetic risks, resulting in lower fitness than fixed rules. These fragile strategies might therefore be unlikely to evolve in the first place. Heterogeneous resource availability favored more cautious (and thus more robust) strategies, particularly when knowledge of resource variation was accurate. Our results demonstrate that the assumptions regarding the dynamic trade-offs underlying an individual’s decision-making can have important consequences for predicting the effects of anthropogenic stressors on wildlife populations.
Differences in the Loin Tenderness of Iberian Pigs Explained through Dissimilarities in Their Transcriptome Expression Profile

Simple Summary The Iberian pig is the most representative autochthonous breed of the Mediterranean region with unique genetic and phenotypic characteristics. The breed has been successfully preserved by its high-quality meat and high-priced products. Tenderness is one of the most relevant meat quality traits, and meat tenderization is influenced by genetic and environmental effects such as pre-slaughter handling and post-mortem conditions. Tenderness could be included in Iberian pig breeding programs, mainly focused on the improvement of premium-cuts percentage, in order to avoid the meat quality decline. A better biological understanding of this trait is needed. In the current study, we analyze the transcriptome of pigs divergent for Warner–Bratzler shear force through RNA-seq technique for the identification, characterization and quantification of candidate genes involved in biological pathways, networks and functions affecting meat tenderness. Abstract Tenderness is one of the most important meat quality traits and it can be measured through shear force with the Warner–Bratzler test. In the current study, we use the RNA-seq technique to analyze the transcriptome of Longissimus dorsi (LD) muscle in two groups of Iberian pigs (Tough and Tender) divergent for shear force breeding values. We identified 200 annotated differentially expressed genes (DEGs) and 245 newly predicted isoforms. The RNAseq expression results of 10 genes were validated with quantitative PCR (qPCR). Functional analyses showed an enrichment of DE genes in biological processes related to proteolysis (CTSC, RHOD, MYH8, ACTC1, GADD45B, CASQ2, CHRNA9 and ANKRD1), skeletal muscle tissue development (ANKRD1, DMD, FOS and MSTN), lipid metabolism (FABP3 and PPARGC1A) and collagen metabolism (COL14A1). The upstream analysis revealed a total of 11 transcription regulatory factors that could regulate the expression of some DEGs. Among them, IGF1, VGLL3 and PPARG can be highlighted since they regulate the expression of genes involved in biological pathways that could affect tenderness. The experiment revealed a set of candidate genes and regulatory factors suggestive to search polymorphisms that could be incorporated in a breeding program for improving meat tenderness.
Grounded in Culture: Reflections on Sitting Outside the Circle in Community-Based Research With Indigenous Men

Research continues to be a dirty word for many Indigenous people. Community-based participatory research (CBPR) is a means to disrupt power dynamics by engaging community members within the research process. However, the majority of relationships between researcher and participants within CBPR are structured within Western research paradigms and they often reproduce imbalances of power. The purpose of this article is to reflect on the process of CBPR within a research project focused on Indigenous men’s masculinity and mental health. In doing so, we aim to contribute to reflexive practice in CBPR and flatten research hierarchies to facilitate more equitable knowledge sharing. Our reflections highlight the importance of prioritizing healing, centering cultural protocols, negotiating language, and creating space for Indigenous research partners to lead. These critical lessons challenge Western researchers to ground their practices in Indigenous culture while they “sit outside the circle” to facilitate more equitable and engaged partnerships.
Versatile Network Codes: Energy Consumption in Heterogeneous IoT Devices

In an Internet of Things (IoT), the number of interconnected devices is huge and has been increasing drastically. Their generated data requires powerful aggregated computing resources and consumes enormous energy for processing and transmission. Having said that, most IoT devices are very limited and heterogeneous in computing capabilities, causing a big challenge for designing a commonly used interconnect that is both reliable and energy-efficient. Random Linear Network Coding (RLNC) schemes have proven its capability both theoretically and in practical deployment not only to increase throughput and reliability but also to reduce latency and energy consumption. However, it is unclear how different variations of RLNC, in particular, Fulcrum codes aimed for heterogeneous devices perform in heterogeneous IoT settings. In this paper, we conduct a measurement campaign, allowing for a fair comparison among the state of the art RLNC families, with regard to energy consumption, decoding probability, and goodput. The study provides insights and guidelines for applying RLNC schemes to data transmission in heterogeneous IoT networks.
Piecewise Adaptive-Norm Trend Filtering Method for ICESat/GLAS Waveform Data Denoising

The Geoscience Laser Altimeter System (GLAS) aboard Ice, Cloud and land Elevation Satellite (ICESat) was able to capture the full waveform of backscattered laser pulse. However, the accuracy of the surface information extracted from the waveform was vulnerable to background noise. In this paper, a piecewise adaptive <inline-formula> <tex-math notation="LaTeX">$l_{q}$ </tex-math></inline-formula> <italic>-norm</italic> trend filtering method is proposed for the GLAS full waveform denoising on the basis of trend filtering. To minimize the loss of useful signal while removing the noise, the proposed method adaptively assigns different norms to the smooth constraints according to the local signal energy. The filtered results can then be obtained by iteratively minimizing the hybrid-norm loss function. The proposed method is tested on both the simulated waveforms and real GLAS waveform data. In the simulated experiments, the quantitative evaluation is conducted with the filtered waveforms, as well as the results after waveform decomposition. For comparison, the most commonly used waveform filtering methods, i.e. Gaussian filtering, wavelet transform, Empirical model decomposition and <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math></inline-formula> trend filtering, are involved in the experiments. The results show that the proposed method outperforms the mainstream methods on waveform filtering, in terms of removing noise and preserving the shape and energy amplitude of the GLAS waveforms.
PPB: a Path-based Packet Batcher to Accelerate Vector Packet Processor

Fast Data I/O (FD.io) is an open project to promote network processing based on generic hardware platforms, providing a feasible path to accelerate Network Function Virtualization (NFV). As the core of FD.io, vector packet processor (VPP) is a modularized and high-performance software framework for building network data plane applications. The core idea of VPP has two parts. Firstly, VPP processes a group of packets (packet vector) every time to reduce the instruction cache (i-cache) misses with vectorized processing model. Secondly, VPP decreases the data cache (d-cache) misses by prefetching the following packets. We observe that the received packet order has a significant impact on the performance of VPP. When the packets within a vector traverse different paths, the vector would be split into multiple small vectors. The frequency of i-cache and d-cache misses would increase.In this paper, we design a model to quantify the overhead in VPP. The key point to reduce the overhead is to decrease the number of processing paths in a vector. We propose a Path-based Packet Batcher (PPB) to accelerate VPP by adjusting the packet order. Before VPP processing packets, PPB batches the packets based on the processing paths they will traverse. We build a PPB prototype based on FPGA to evaluate the performance optimizations. The experimental results show that the reduction of i-cache and d-cache misses can be up to 57.6% and 17% respectively.
Probabilistic Smoothing Based Generation of a Reliable Lane Geometry Map With Uncertainty of a Lane Detector

Since lane geometry information can be used for controlling the pose of an intelligent vehicle, a lane geometry map that contains the lane geometry information should have reliable accuracy. For generating the reliable lane geometry map, lane curve which is detected from a lane detector is an useful information because the lane geometry information can be obtained directly. However, since the detected lane curve contains an uncertainty caused by the noise of the lane detector, the accuracy of the lane geometry map can be degraded. In previous studies, a near point on each detected lane is sampled at each time stamp and accumulated for reducing the noise effects of the lane detector. However, these sampled points also contain the sensing noise of the lane detector and the density of accumulated points depends on the distance interval of data acquisition. In this article, we proposed the probabilistic lane smoothing-based generation method for the reliable lane geometry map. In the probabilistic lane smoothing, the lane geometry map is modeled as the nodes with the uncertainty of its position obtained from the sensor error model. Each node of the lane geometry map is smoothed based on the Bayesian filtering scheme. The evaluation results show that the lane geometry map can be generated by reducing the noise of the detected lane curve. Additionally, the generated lane geometry map is more reliable than the sampling point-based generated map in terms of the accuracy of the distance and heading angle.
Tuning monoclonal antibody galactosylation using Raman spectroscopy‐controlled lactic acid feeding

A key aspect of large‐scale production of biotherapeutics is a well‐designed and consistently‐executed upstream cell culture process. Process analytical technology tools provide enhanced monitoring and control capabilities to support consistent process execution, and also have potential to aid in maintenance of product quality at desired levels. One such tool, Raman spectroscopy, has matured as a useful technique to achieve real‐time monitoring and control of key cell culture process attributes. We developed a Raman spectroscopy‐based nutrient control strategy to enable dual control of lactate and glucose levels for a fed‐batch CHO cell culture process for monoclonal antibody (mAb) production. To achieve this, partial least squares‐based chemometric models for real‐time prediction of glucose and lactate concentrations were developed and deployed in feedback control loops. In particular, feeding of lactic acid post‐metabolic shift was investigated based on previous work that has shown the impact of lactate levels on ammonium as well as mAb product quality. Three feeding strategies were assessed for impact on cell metabolism, productivity, and product quality: bolus‐fed glucose, glucose control at 4 g/L, or simultaneous glucose control at 4 g/L and lactate control at 2 g/L. The third feeding strategy resulted in a significant reduction in ammonium levels (68%) while increasing mAb galactosylation levels by approximately 50%. This work demonstrated that when deployed in a cell culture process, Raman spectroscopy is an effective technique for simultaneous control of multiple nutrient feeds, and that lactic acid feeding can have a positive impact on both cell metabolism and mAb product quality.
WhatsApp video call communication between oncological patients and their families during Covid-19 outbreak.

BACKGROUND On March 8th, 2020 the Italian Government implemented extraordinary measures to limit COVID-19 viral transmission. The aim of the study was to verify if the use of WhatsApp facilitates communication, improves health information, perception of safe and security, reduce emotional stress during the COVID-19 emergency. METHODS In this study we identified two period, in the pre-COVID 1-month period (February 9th-March 8th, 2020) 34 patients underwent elective surgery for malignancies (21) and benign (13) diseases, respectively. We daily given to families of patients clinical information face-to-face in the ward regarding their postoperative course. In the post-COVID 1-month period (March 9th - April 5th, 2020), 15 patients with malignancies were treated. In this period, patients and their families given a consent form to let the surgical team to communicate clinical data using WhatsApp. At the end of the study period we collected a satisfaction anonymous questionnaire of both patients and families. RESULTS Statistically significant differences were observed in the pre- vs post- COVID period regarding the number of surgical procedures (p = 0.004). In the post-COVID period, the satisfaction questionnaire showed a good reliability (Cronbach's alpha 0.912) and a high percentage of satisfaction of patients and their families for the adopted communication tool, reassurance, privacy protection and reduction of emotional stress. CONCLUSIONS WhatsApp is a safe and fast technology, it offers the opportunity to facilitate clinical communications, reduce stress, improve patient security, obtain clinical and psychological positive implications in patient's care preserving their privacy in the COVID-19 emergency period.
Migration of surrogate contaminants from paperboard to foods: Effect of food and surrogate properties

ABSTRACT The current research describes an alternative test method to evaluate the impact of food properties and compound characteristics on migration from paperboard to food. Tightly sealed bottles containing paperboard spiked with surrogate components as a donor, together with modified polyphenylene oxide (MPPO or Tenax®) or one of the nine considered foods as a receptor, were stored at 22°C. Instead of analysing the receptor, migration from donor to receptor was followed up by evaluating the recovery of surrogates from the donor over time, thus avoiding challenges in the analysis of the foods as such. Free fat content affected the migration more than the specific surface area of the food, reaching a plateau at fat contents >8.1%. The highest migration was observed to fatty foods such as biscuits (8% to 25% fat) and chocolate (40% fat). Intermediate migration occurred to starchy and particulate foods such as egg-based wheat pasta (2.6% fat), wheat flour (1% fat) and rice flour (0.5% fat). Low migration occurred in the case of paperboard in contact with wheat pasta (0.4% fat). Native starch was found to be more sensitive to migration than gelatinised starch. Volatility was identified as the most important characteristic of the migrating compounds. MPPO was considered as a suitable surrogate for dry foods as it did not underestimate migration in any case. However, for low-fat foods such as wheat pasta, clear overestimations could occur, but only for volatile surrogates with vapour pressure over 1.45 mTorr.
Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning

In this review, we aim to assess the current state of science in relation to the integration of patient‐generated health data (PGHD) and patient‐reported outcomes (PROs) into routine clinical care with a focus on surgical oncology populations. We will also describe the critical role of artificial intelligence and machine‐learning methodology in the efficient translation of PGHD, PROs, and traditional outcome measures into meaningful patient care models.
Coaxial printing of double-layered and free-standing blood vessel analogues without ultraviolet illumination for high-volume vascularised tissue

Human umbilical vein endothelial cells (HUVECs) and human aortic smooth muscle cells (HASMCs) were coaxially and continuously extruded without ultraviolet illumination using a microfluidic-based nozzle. Type I collagen (3 mg ml−1) containing HUVECs and a crosslinking reagent (100 mM CaCl2) were supplied as the core material. A mixture of 3 mg ml−1 of type I collagen (25%) and 1.8% weight volume−1 of sodium alginate (75%) was provided as the shell layer material surrounding the core material. The HUVECs were well proliferated at the core and reshaped into a monolayer formation along the axial direction of the scaffold. The HASMCs showed more than 90% cell viability in the shell layer. Fluorescent beads were passed through the inside channel of the scaffold with the HUVEC core and HASMC shell using an in-house connector. This double-layered scaffold showed higher angiogenesis in growth factor-free medium than the scaffold with only a HUVEC core. The HASMCs in the shell layer affected angiogenesis, extracellular matrix secretion, and outer diameter. The proposed technique could be applied to three-dimensional bioprinting for the production of high-volume vascularised tissue.