Miracle-dz/UniFAR-FTUs huggingface dataset:
Forwarding Strategies for Named Data Networking Based IoT: Requirements, Taxonomy, and Open Research Challenges

The Internet of Things (IoT) aims to efficiently connect various entities, including humans, machines, smart devices, physical environments, and others, so they can communicate and exchange data in real time. However, due to the massive amount of data transferred, the presence of devices with limited resources, heterogeneity, and mobility support would make it difficult to create a robust network with respect to performance in an IoT context. In order to efficiently disseminate the enormous volume of automated data, Named Data Networking (NDN), a viable networking design for the future Internet, has been proposed. NDN has shown great potential for IoT because it has built-in support for naming, caching, mobility, and security. Forwarding strategies play an important role in the successful deployment of NDN-based IoT. In this article, we introduce NDN-based IoT forwarding emphasizing on IoT characteristics and requirements. We classify NDN-based IoT forwarding strategies and then discuss in detail certain exemplary schemes. Additionally, we compare several aspects of current forwarding methods that are now in use, including the types of forwarding strategy, particular issues, type of solution, assessment metrics, and simulation platform. We wrap up our contribution by outlining the major open research issues that can guide future investigations in this area. We anticipate that this survey will help the community of NDN-based IoT researchers’ understanding of forwarding strategies in IoT environments.
Aboveground biomass stock and change estimation in Amazon rainforest using airborne light detection and ranging, multispectral data, and machine learning algorithms

Abstract. Developing an efficient method to accurately estimate aboveground biomass in tropical forests is critical to monitoring the carbon stock and implementing policies to reduce emissions caused by deforestation. Thus, the objective of the present study was to estimate aboveground biomass in areas of the Amazonian Forest with selective logging, using the random forest (RF), support vector machine (SVM), and artificial neural network (ANN) machine learning algorithms, using light detection and ranging (LiDAR) data and these combined with OLI/Landsat 8 variables, as well as mapping the biomass for the years 2014 and 2017, allowing one to analyze its dynamics between the years of analysis. The RF and SVM algorithms obtained the lowest error values in all datasets. The association of the variables increased the RF performance. Analyzing the dynamics of biomass, it was observed that the oldest exploration units (2006, 2007, and 2008) have lower biomass stocks. The highest biomass losses in 2017 came from units operated between 2012 and 2013 (the most recent record). Thus, with the method used in this study, it was possible to infer that the machine learning algorithms were efficient in estimating the biomass, emphasizing the RF and the SVM.
Comparison of Cluster Formation Algorithms Based on Fuzzy Logic Rules

In Mobile Ad-hoc Networks (MANET's), clustering is one of the best approaches to deal with the communication issues arising in the transmission of the packets from source to destination. The complete network is divided into the number of clusters and members in each cluster operate under the supervision of a node called cluster head thus, it becomes important to partition the network effectively so that maximum number of nodes can be covered by using a particular cluster head. Different strategies have been proposed till date. In this paper an earlier proposed strategy called Ant colony Based Cluster head selection algorithm have been compared to the existing lowest id based algorithm using the fuzzy logic rules.
Complications Rate of Conventional Percutaneous Nephrolithotomy (PCNL) in a tertiary care center

Aim: To observe the complication rate of conventional percutaneous nephrolithotomy (PCNL) in a tertiary care Hospital. Methods: This Retrospective study conducted from January 2016 to January 2020 in the Department of Urology at Lady Reading Hospital in Peshawar, Pakistan.The research included a total of 449 patients who underwent conventional PCNL.Non-contrast CT KUB was performed on all patients before surgery. After passing 6fr Ureteric catheter through a cystoscope in lithotomy position patient was then shifted into prone position. Under the guidance of fluoroscopy, all procedures were carried out while the patient was lying flat and conventional 30FR amplatz sheath was used as working channel. Results: Complications were reported in 46.9% of cases.The majority of the complications occurred in patients with clavien grades I and II, with 120(27%) and 54(12%) patients, respectively. In Grade I complicationstransient feveroccurred in 67(15%) patients treated with antipyretics while 53(12%) patients had nephrostomy site leakage managed with simple pressure dressing at bed site. In grade II complication 45(10%) patients had bleeding which required transfusion and 9(2%) patients developed sepsis treated with parenteral antibiotics. 10(2%) patients developed grade IIIa complication such as persistent bleeding in 4(0.8%) patients managed with percutaneous angioembolization and 6(1.2%) patients required percutaneous drainage of perinephric collection. 25(5.5%) patients had grade IIIb complications, in 24( 5.3%) patients DJ stenting was done for PCS injury or persistent leakage from nephrostomy site while 1(0.2%) patient needed colostomy for colonic injury. Conclusion: The chance of serious complications during percutaneous nephrolithotomy is very minimal. It is also safe, cost effective and well-tolerated. Transient fever or nephrostomy site leakage are the most frequently occurring minor complications often subside spontaneously. Keywords: Nephrostomy, percutaneous nephrolithotomy
Engineering Students’ Perception of Learner Agency Development in an Intercultural PBL (Problem- and Project-Based) Team Setting

Contribution: This study explores the elements engineering students perceive as important for developing their learner agency in the context of intercultural project-based learning (PBL) teams. Background: The concept of learner agency has recently gained prominence due to its relevance for student-centeredness, autonomy, self-regulation, and collaboration. Certain pedagogical approaches are known to specifically support the development of learner agency, including PBL, in which learners are provided with active, self-directed, and collaborative learning tasks. PBL practice is also increasingly diverse, emphasizing intercultural collaboration in teams. However, learner agency has received little research attention in PBL settings, and even less in intercultural PBL. This study contributes to the existing literature on the development of learner agency in intercultural PBL teams. Research Question: What elements do engineering students consider important for supporting their learner agency development in an intercultural PBL team context? Methodology: Theoretically, learner agency is framed within three interrelated dimensions, namely, intrapersonal, behavioral, and environmental. Based on this framework, a survey instrument with 31 items was constructed and responses were obtained from 310 engineering students. The survey used expert review, student piloting, exploratory factor analysis (EFA), and Cronbach’s alpha to test content validity, construct validity, and reliability. The descriptive and demographic statistics were examined through $t$ -test and the analysis of variance test. Findings: Five factors emerged from EFA: 1) interest and motivation; 2) self-efficacy; 3) self-regulated behaviors in teams; 4) team dynamics; and 5) external support. The statistical analysis shows that the interest and motivation factor was perceived by the engineering students as the most important. Furthermore, several demographic variables, including gender, nationality, year of study, and type of PBL learner based on their level of experience with PBL, were found to impact engineering students’ agency development.
Beam Management Technique For 5G Wireless Communication: A Deep Learning Approach

The expectation from next-generation 5G technology is to satisfy data-hungry applications such as vehicular applications and augmented and virtual reality. 5G along with millimeter-wave technology is a prominent technology that can satisfy user demands and needs as it provides a high data rate. The accomplishment of a high data rate is possible using a large number of antennas. However, the increased number of antennas results in increased path loss. Apart from increased path loss, beam misalignment is another challenge that can be overcome by robust beam forming techniques. Beam management involves providing a comprehensive solution to various challenges associated with the beam. This paper provides an overview of beam management procedures using deep learning to reduce beam alignment problems. Beam management includes various steps such as channel state estimation, beam training, beam selection, beam alignment, and beamforming. Based on the analysis, the paper also provides a comprehensive framework for improved beam management. Finally, the paper also discusses the open issues in this field of work.
Design and Optimization of Wheatstone Bridge Adjustment Circuit for Resistive Sensors

A novel Wheatstone bridge adjustment circuit with both rough-tuning and fine-tuning functions is designed for balancing the Wheatstone bridge in this article. Firstly, the parametric circuit structure is constructed to facilitate the design of rough-tuning and fine-tuning sub-circuit parameters; Secondly, the quantitative index of Wheatstone bridge imbalance is defined, and the parameter design flow of the rough-tuning sub-circuit, which consists of two sets of series-parallel-resistor (SPR) structures that are, respectively, connected in parallel with the two branches of one half-bridge, is given to directly weaken the initial bridge imbalance in the manufacturing stage. Theoretical analysis results show that the SPR structure can effectively approach any expected value and reduce the number of fixed resistor types. Thirdly, parameters of the fine-tuning sub-circuit, which consists of a resistor and a digital-to-analog converter (DAC), are optimized based on any expected adjustable range. Adjusting the DAC input to seek the middle value of an analog-to-digital converter (ADC) output, indirectly eliminates the additional bridge imbalance caused by mechanical assembly stress, gravity, ambient temperature, etc., in the application stage. Then the influence of the fine-tuning parameters on linear fitting coefficients of the output versus input of the Wheatstone bridge is analyzed theoretically. The results show that the DAC output voltage only has a significant linear impact on the intercept coefficient, while its impact on the scale coefficient is negligible. Finally, the effectiveness of the adjustment circuit is verified on a six-axis force/torque sensor that is developed for an Experimental Module Manipulator (EMM) in the Chinese Space Station (CSS).
Differentiability of the Solutions of a Semilinear Abstract Cauchy Problems With Respect to Parameters

The Frechet difierentiability with respect to a parameter q of the solutions z(t;q) of Cauchy problems of the form d dt z(t) = A(q)z(t) + F(q;t;z(t)) is analyzed. Su-cient conditions on the operator A(q) and on F are derived and the corresponding sensitivity equations for the Frechet derivative Dqz(t;q) are found.
Detection of rotational CO emission from the red-supergiants in the Large Magellanic Cloud

Abstract It is yet well understood how mass-loss rates from evolved stars depend on metallicities. With a half of the solar metallicity and the distance of only 50 kpc, the evolved stars of the Large Magellanic Cloud (LMC) are an ideal target for studying mass loss at low metallicity. We have obtained spectra of red-supergiants in the LMC, using the Hershel Space Observatory, detecting CO thermal lines fro J=6–5 up to 15–14 lines. Modelling CO lines with non-LTE Radiative transfer code suggests that CO lines intensities can be well explained with high gas-to-dust ratio, with no obvious reduction in mass-loss rate at the LMC. We conclude that the luminosities of the stars are primary factors on mass-loss rates, rather than the metallicity.
The effect of skewing on the vorticity produced by an airjet vortex generator

Abstract The vorticity production by a single vortex generator jet in a turbulent boundary layer at high speed and zero pressure gradient was studied by analysing surface-flow patterns. The investigation involved a range of jet mass flow rates and skew angles while the freestream Mach number and jet pitch angle were held constant. A qualitative analysis of the skin friction patterns demonstrated the effective role of the skew angle as a bifurcation parameter. The vortex production is classified into three main regimes as the skew angle increases from zero (fully downstream) to 180° (fully upstream). Better understanding of the physical mechanism behind the transition from the first regime to the second is crucial in the design of the airjet vortex generator.
HEAT STRESS AND MILK PRODUCTION IN THE FIRST PARITY HOLSTEINS – THRESHOLD DETERMINATION IN EASTERN CROATIA

In the light of increasingly rapid climate change worldwide, one of the primary goals is to reduce financial losses of dairy farmers and to enable the sustainable farming. In order to realize those goals, the necessity of implementation of breeding values for heat resistance in breeding strategies, have become more and more pronounced. Estimation of breeding values requires determination of temperaturehumidity index (THI) threshold value. Therefore, the objective of this research was to determine the THI threshold value for the first parity Holsteins in environmental conditions in Eastern Croatia. With that purpose individual test-day records of the first parity Holsteins with records of ambient temperature and relative humidity in the barns were analysed. Data were collected in regular milk recording from January 2006 to December 2012. The THI threshold values for daily milk yield were determined by least square analyses of variance for each given THI value (from 65 to 76) using the PROC MIXED (SAS). The THI< 68 did not cause significant change in daily milk production of the first parity Holsteins. Significant decrease of daily milk yield was observed at THI ≥ 68 with estimated drop from 0.240 to 0.716 kg milk/day (THI from 68 to 76). The THI=68, as the lowest value at which significant decrease in daily milk yield was determined, was taken as the threshold value for the first parity Holsteins in Eastern Croatia.
Robust Scan Registration for Navigation in Forest Environment Using Low-Resolution LiDAR Sensors

Automated forest machines are becoming important due to human operators’ complex and dangerous working conditions, leading to a labor shortage. This study proposes a new method for robust SLAM and tree mapping using low-resolution LiDAR sensors in forestry conditions. Our method relies on tree detection to perform scan registration and pose correction using only low-resolution LiDAR sensors (16Ch, 32Ch) or narrow field of view Solid State LiDARs without additional sensory modalities like GPS or IMU. We evaluate our approach on three datasets, including two private and one public dataset, and demonstrate improved navigation accuracy, scan registration, tree localization, and tree diameter estimation compared to current approaches in forestry machine automation. Our results show that the proposed method yields robust scan registration using detected trees, outperforming generalized feature-based registration algorithms like Fast Point Feature Histogram, with an above 3 m reduction in RMSE for the 16Chanel LiDAR sensor. For Solid-State LiDAR the algorithm achieves a similar RMSE of 3.7 m. Additionally, our adaptive pre-processing and heuristic approach to tree detection increased the number of detected trees by 13% compared to the current approach of using fixed radius search parameters for pre-processing. Our automated tree trunk diameter estimation method yields a mean absolute error of 4.3 cm (RSME = 6.5 cm) for the local map and complete trajectory maps.
Trade vs. daily press: the role of news coverage and sentiment in real estate market analysis

ABSTRACT Each week, thousands of newspaper articles on real estate topics are read by market participants. While the market is comparatively intransparent, readers hope to find valuable information. This raises the question of whether this investment of time pays off and whether different types of newspapers are an equivalent source of information. This paper examines the relationship between news-based coverage of real estate topics respectively news-based market sentiment and total returns of the asset classes of residential, office and retail. Using methods of natural language processing, including word embedding, topic modelling and sentiment analysis, three sentiment indicators for each asset class can be derived from 137,000 articles of two trade and two daily newspapers. Our results suggest that trade newspapers outperform daily newspapers in the prediction of future total returns and that the generated sentiment indicators Granger-cause total returns. Moreover, the results indicate that daily newspapers report more negatively on rising returns in the residential market than the trade press. To the best knowledge of the authors, this is the first study to quantify news coverage and sentiment for the main real estate asset classes through means of textual analysis, and to assess different sentiments in trade and daily press.
“I Study When All My Family is Asleep”. Gender, Time and Space in Online Education in the COVID-19 Pandemic,

Abstract The COVID-19 pandemic has radically altered the ways of working, studying, and interacting globally, forcing people and communities to reinterpret their daily activities. This study analyzes the changes experienced by working mothers who began distance studies at an Argentine university during the second year of the pandemic. Results indicated how spaces and time were transformed, and gender inequalities deepened. The pandemic, above all, impacted the positions and negotiations that working mothers managed to establish to continue studying in a virtual university environment. In these cases, conquering time and space for learning is, at the same time, an act of acceptance and innovation as a woman.
Design of a Novel Lunar Transportation System (FLOAT) consisting of Diamagnetically-Levitated Robots on a Flexible Film Track

A durable, long-life robotic transport system will be critical to the daily operations of a sustainable lunar base in the 2030's, as envisioned in NASA's Moon to Mars plan and mission concepts like the Robotic Lunar Surface Operations 2 (RLSO2), to transport regolith mined for ISRU consumables (H2O, LOX, LH2) or construction, and transport payloads around the lunar base and to / from landing zones or other outposts. In this work, we present component analysis, preliminary experimental results, and system designs for a novel lunar transportation system, FLOAT (Flexible Levitation on a Track), that leverages diamagnetically levitated robots. Unlike current lunar robot concepts that use wheels (SEV, RASSOR), legs (Spidernaut), or hybrid wheels-on-legs for mobility, FLOAT robots are solid-state (no motors, gearboxes, or other moving parts) and consist only of permanent magnets connected in planar arrays levitating to minimize lunar dust abrasion / wear over a flexible PCB track that generates electromagnetic thrust. Results show that FLOAT robots can maintain extremely low power requirements over a range of terrains – using <5 W/m2 or <0.15 W/kg to carry up to 30 kg/m2 payload on tracks with slopes <40° and curves >5 m in-plane radius or >25 m out-of-plane radius – and use 10-100x less power for transport than wheeled vehicles. For initial system deployment, we designed track deployments robots which can leverage existing lunar robotic systems to un- roll segments of FLOAT tracks onto the lunar regolith. Finally, system design analysis shows the FLOAT concept can serve as a complete transportation system to satisfy the volumetric flow requirements of the RLSO2 mission concept.
On Convergence of the Distributions of Statistics With Random Sample Sizes to Normal Variance-Mean Mixtures

We prove a general transfer theorem for multivariate random sequences with independent random indexes in the double array limit setting. We also prove its partial inverse providing necessary and sufficient conditions for the convergence of randomly indexed random sequences. Special attention is paid to the case where the elements of the basic double array are formed as statistics constructed from samples with random sizes. Under rather natural conditions we prove the theorem on convergence of the distributions of such statistics to multivariate normal variance-mean mixtures and, in particular, to multivariate generalized hyperbolic laws.
Analysis of Simplifications Applied in Vibration Damping Modelling for a Passive Car Shock Absorber

The paper presents results of research on hydraulic automotive shock absorbers. The considerations provided in the paper indicate certain flaws and simplifications resulting from the fact that damping characteristics are assumed as the function of input velocity only, which is the case of simulation studies. An important aspect taken into account when determining parameters of damping performed by car shock absorbers at a testing station is the permissible range of characteristics of a shock absorber of the same type. The aim of this study was to determine the damping characteristics entailing the stroke value. The stroke and rotary velocities were selected in a manner enabling that, for different combinations, the same maximum linear velocity can be obtained. Thus the influence of excitation parameters, such as the stroke value, on force versus displacement and force versus velocity diagrams was determined. The 3D characteristics presented as the damping surface in the stoke and the linear velocity function were determined. An analysis of the results addressed in the paper highlights the impact of such factors on the profile of closed loop graphs of damping forces and point-type damping characteristics.