Miracle-dz/UniFAR-FTUs huggingface dataset:
Household appliance usage recommendation based on demand forecasting and multi­objective optimization

Accelerated population growth in the 21st century and increased demand for energy sources, associated with climate change, have resulted in two main challenges: the search for sustainable energy sources and the need to find more efficient ways to use extant sustainable sources. The forecasting module provides an estimate of the future usage of these appliances and it is the source of the recommended module’s suggestion. Time Series Forecasting techniques, such as Autoregressive Integrated Moving Average, Long­Short Term Memory (LSTM), Gated Recurrent Units, Echo State Networks (ESN), and Support Vector Regression, were tested for the predictive module. Multi­objective optimization techniques such as Non­Sorted Genetic Algorithm II (NSGA II), Multi­Objective Particle Swarm Optimization (MOPSO), Speed constrained Multi-­objective Particle Swarm Optimization (SMOPSO), and Strength Pareto Evolutionary Algorithm two (SPEA2), for example, were tested for the Recommendation Module. The Forecasting and Recommendation module experiments were performed independently. In the Forecasting Module, the results and statistical tests revealed LSTM as the best­ suited technique for forecasting the loads of the majority of the appliances tested (in this case seven) in terms of root mean square error. In the experiments performed for the recommendation module, NSGA II showed a higher overall performance compared to other metrics in terms of hyper volume of the Pareto Front generated. This work presents the potential of using both Predictive Models and Multi­Objective Optimization Techniques combined to reduce energy usage in household environments.
Automated Annotator Variability Inspection for Biomedical Image Segmentation

Supervised deep learning approaches for automated diagnosis support require datasets annotated by experts. Intra-annotator variability of a single annotator and inter-annotator variability between annotators can affect the quality of the diagnosis support. As medical experts will always differ in annotation details, quantitative studies concerning the annotation quality are of particular interest. A consistent and noise-free annotation of large-scale datasets by, for example, dermatologists or pathologists is a current challenge. Hence, methods are needed to automatically inspect annotations in datasets. In this paper, we categorize annotation noise in image segmentation tasks, present methods to simulate annotation noise, and examine the impact on the segmentation quality. Two novel automated methods to identify intra-annotator and inter-annotator inconsistencies based on uncertainty-aware deep neural networks are proposed. We demonstrate the benefits of our automated inspection methods such as focused re-inspection of noisy annotations or the detection of generally different annotation styles using the biomedical ISIC 2017 Melanoma image segmentation dataset.
Scrutinizing Pork Price Volatility in the European Union over the Last Decade

Simple Summary The volatility of prices for agricultural products is of great importance for both producers (due mainly to continued optimization of the production process) and consumers. We analyzed long-term trends as well as cyclical, seasonal, and irregular fluctuations in pork prices in European Union (EU) countries. Despite the existence of the EU common market, there is considerable spatial variation in pork prices between member states. Pork prices in the EU are characterized by seasonality and are generally higher than average in summer and lower in winter. Considering risk management in agribusiness, the nature of price fluctuations, their amplitude, and period are of paramount importance. Regular seasonal changes or long-term trends can be considered during the decision-making process, but short-term and randomly occurring fluctuations and medium-term changes with large deviations from the expected prices constitute a serious risk. Abstract The aim of this study was to analyze the factors that can influence pork prices, particularly the effects of various types of fluctuations on the volatility of pork prices in the European Union as a whole market and individual EU countries. The research material consisted of monthly time series of pork prices collected from 2009 to 2020. These data originated from the Integrated System of Agricultural Information coordinated by the Polish Ministry of Agriculture. Information on global pork production volumes is from the Food and Agriculture Organization Statistics (FAOSTAT) database. Time series of prices were described by the multiplicative model, and seasonal breakdown was performed using the Census X-11 method. The separation of the cyclical component of the trend was performed using the Hodrick–Prescott filter. In 2019, pork production in the European Union totaled 23,954 thousand tonnes, which accounted for 21.8% of global pork production. The largest producers were Germany, Spain, and France, supplying more than half of the pork to the entire European Union market. Pork prices in the EU, averaged over the 2009–2020 period were Euro (EUR) 154.63/100 kg. The highest prices for pork were recorded in Malta, Cyprus, Bulgaria, and Greece, whereas the lowest prices in Belgium, the Netherlands, Denmark, and France. The breakdown of the time series for pork prices confirmed that, in the period from 2009 to 2020, pork prices exhibited considerable fluctuations of both a long-term and medium-term nature as well as short-term seasonal and irregular fluctuations. Prices were higher than average in summer (with a peak in June–August) and lower in winter (January–March). Overall, the proportions of different types of changes in pork prices were as follows: random changes—7.9%, seasonal changes—36.6%, and cyclical changes—55.5%.
CAUSATIVE FACTORS OF CONSTRUCTION WASTE GENERATION IN MALAYSIA

This is a research book based on a study conducted to identify the significant causative factors to construction waste generation in Malaysia construction industry. This book describes the research process which includes data analysis in a systematic manner and is organised in four chapters as follows: Chapter 1: Concern of waste generation in construction industry. It covers the classification of the wastes, causes and effects of the generated wastes and also the disposal issues. Chapter 2: Identification on causative factors of construction wastes generation. These factors are identified from previous researches related to construction waste that were carried. Chapter 3: Questionnaire survey on identifying the significant causative factors of construction waste generation in Malaysia construction industry. It describes the design of the questionnaire, implementation of the survey and also the analysis of the collected data. Chapter 4: Development of structural equation model which indicates the structural relationship of causative factors toward the construction waste generation using the multivariate approach.
A novel generic modulo‐2 graph with full set taxonomical conversion to parallel prefix adders

This paper proposes a novel generic modulo‐2 graph that can be converted to parallel prefix adders (PPA). Also, a conversion algorithm for converting the proposed graph to PPAs is proposed in this paper. The conversation algorithm can be applied on N‐bit Generic modulo‐2 graph, and this graph is converted to N‐bit PPAs. When the proposed conversion algorithm is applied to generic modulo‐2 graph, this graph is converted to Brent‐Kung, Sklansky, Kogge‐Stone, Harris, Ladner‐Fischer, Han‐Carlson, and Knowles adders. Moreover, PPAs are shown in trilinear coordinates to represent the final PPAs, which generic graph converted to them. Furthermore, the add operation is done by generic graph and also the correctness of add function of this graph is investigated by “Boolean decision diagram. ”
Frack-Off: Social Media Fights Against Fracking in Argentina

ABSTRACT This article explores how the anti-fracking movements in the province of Mendoza, Argentina, have used Twitter to shape narratives around anti-fracking. Adopting a dynamic view of collective action frames, the article shows that the anti-fracking movements have developed multiple frames to articulate their struggle and justify their grievances, and how procedural injustice and environmental values have been motivational factors for local citizens. The article also demonstrates that Twitter is principally being used as a broadcast platform rather than being used to create online collective action, but that the strong framing means that disparate groups have been united behind the common cause.
THE EFFECT OF HUMAN CAPITAL ON ECONOMIC GROWTH IN SOME SUB SAHARA AFRICAN COUNTRIES (SSA)

Purpose: This research looked into debate on the possible impact of human capital on economic growth in Sub-Saharan Africa (SSA) and considers two alternative measures of human capital: health and education. Methodology: The research used a dynamic model based on the system generalized method of moments (SGMM) and analysed a balanced panel data covering 35 countries from 1986–2018. The research used Microsoft excel to record all the data gotten from the world indicator data base from world bank, penn world table data base and CANA database. The analysis was presented in a tabular form. Findings: This study found that human capital has an overall positive and statistically significant impact on economic growth in the SSA region, although, democracy has a negative and statistically significant impact on economic growth in the region. This finding shows the importance of both measures of human capital and aligns with the argument in the literature that neither education nor health is a perfect substitute for the other as a measure of human capital. Unique contribution to theory, practice and policy:Generally, the finding emphasised that both education and health measures of human capital are important, and that policymakers must consider the level of economic development while formulating policies that can enhance the impact of human capital on economic growth in the Sub-Saharan Africa region.
Experimental testing of anchoring devices for bottom rails in partially anchored timber frame shear walls

Kallsner and Girhammar have presented a new plastic design method of wood-framed shear walls at ultimate limit state. This method allows the designer to calculate the load-carrying capacity of shear walls partially anchored, where the leading stud is not anchored against the uplift. The anchorage system of shear walls is provided from anchor bolts and hold downs. Anchor bolts provide horizontal shear continuity between the bottom rail and the foundation. Hold downs are directly connected from the vertical end stud to the foundation. When hold downs are not provided, the bottom row of nails transmits the vertical forces in the sheathing to the bottom rail (instead of the vertical stud) where the anchor bolts will further transmit the forces into the foundation. Because of the eccentric load transfer, transverse bending is created in the bottom rail and splitting often occurs. Bottom rail experimentally studied with respect to two primary failure modes, splitting along the bottom of the bottom rail due to cross-wise bending and splitting along the edge side of the bottom rail due forces perpendicular to the grain for the sheathing-to-framing connections. The parameters varied are the location of the anchor bolt, the size of the washer and the orientation of the pith. The bottom rail was subjected to loading perpendicular to grain through one-sided sheathing. In this report the different test series are presented. Three series were conducted depending on the location on the anchor bolt. In each series different sets were studied depending on the size of the washer and in each set the pith was placed upwards or downwards. The tests showed three different failure modes. In addition to the failure modes that the testing program was aimed at, splitting along the bottom or side of the bottom rail, the final failure was due to plastic bending and withdrawal of the sheathing-to-framing nails. The results show that the size of the washer and the position of the bolt have a significant influence on the maximum load and the failure modes. It was found that decreasing the distance of the washer to the loaded edge of the bottom rail increases the maximum load.
Virtual Model Control of a Quadruped Walking Robot

The quadruped robot has an individual actuator at each joint which can result in a non intuitive and difficult control problem. This paper used the technique of virtual model control in the dynamic walking of JTUWM Ⅲ quadruped robot. Virtual model control is a motion control language that uses simulations of imagined mechanical components to create forces, which are applied through real joint torques, thereby creating the illusion that the virtual components are connected to the robot. A virtual model of walking quadruped robot was developed. The real joint actuators are used to mimic virtual actuators. The virtual model control is applied to a physical walking quadruped robot. It makes the control problem more straightforward and successfully compels the robot to walk continuously over level terrain.
An economic approach to road condition assessment using road user feedback: A new model and its application

ABSTRACT Assessing roadway assets condition is the prerequisite of an efficient road management system. It requires participation from the top management, equipment, trained human resources, and dedicated funding. Newfoundland and Labrador have 13,500 lane kilometers of roads, of which almost 7,700 kilometers belong to the local jurisdictions. Local agencies typically consult the Transportation Association of Canada's pavement management guidelines for managing the road networks. But, municipality roads require more specified guidelines considering issues like lack of human resources, equipment, inadequate funding, environmental factors, and public expectations. To better maintain these roads, evaluation of road conditions is the first step. However, a proper evaluation system needs considerable funding, a trained workforce, and necessary equipment. Hence, the idea of using road users’ feedback is introduced in this paper. Citizens from 108 municipalities of the province participated in a feedback survey where they were asked questions about roadway assets condition. The survey resulted in a significant amount of data. First, an exploratory analysis of the road users’ feedback data was conducted. Then, a simple distress-based pavement performance model was developed. This model can be adopted by the local agencies as a simple decision-making tool. To make the model practical, a smartphone application called MUNPave is also introduced in this paper.
Hypersonic Boundary-Layer Instability on a Highly Cooled Cone. Part II: Schlieren Analysis of Boundary-Layer Disturbances

A campaign of hypervelocity experiments was conducted with a blunted 5◦-half-angle cone in the T5 shock tunnel. A modified Z-type schlieren setup was utilized to image the boundary-layer with total enthalpies h0 around 10 MJ/kg and freestream-to-wall temperature ratios T∞/Tw of approximately 5. Second-mode instabilities and transitional behavior in the boundary layer were identified imaged within the field of view between x/L = 0.57 and 0.73. Second-mode wavepackets manifested as alternating dark/light waves beginning right at the wall and permeating up to 30% of the boundary-layer height δ. Spectral analysis of the two lower-Reynolds-number shots demonstrated that these packets could be characterized by peak wavenumbers 315 − 365 m−1 at 10% δ. In the highest-Reynolds-number shot, structures passing out of the boundary layer indicated the beginning of turbulent breakdown. For discrete examples where the onset of these structures was imaged, breakdown appeared to begin at x/L = 0.66. A Gabor-filter-based image analysis indicated that spectral content was transferred out of the boundary layer at disturbance Mach numbers 2.75-3.75. A larger range of wavenumbers, 305− 415 m−1, populated the near-wall content in this transitional shot, and high-wavenumber content up to 450 m−1 was identified outside the boundary layer. It is to be noted that this paper serves as a companion study to that of Ref. [1], which interrogated the same boundary layer with focused-laser differential interferometry (FLDI).
Healthcare Delivery among Yoruba Bonesetters in Southwest Nigeria and the Need for Collaboration with Orthodox Orthopedic Healthcare Services: A Mixed Method Study

This study covers three purposively chosen states; Ogun, Ondo, and Oyo, in southwestern Nigeria. Primary data were collected using three sets of questionnaires. The respondent-driven sampling (RDS) technique was employed in selecting the respondents for the study. A total of 69 traditional bonesetters (TBS), 130 TBS patients, and 15 orthopedic surgeons were interviewed. The study reveals that majority (91.2%) of the TBS in the study area claimed that they had received an average of 11 patients from orthodox hospitals in the year preceding the survey while about 9.0% of the respondents reported that 78 Soladoye S. Asa, Matthew O. Ilori, and Lawrence A. Akinyoola they had on the average advised 6 patients per year to relocate to orthodox hospitals. The study also reveals the views of TBS areas of need from government to include recognition (93.7%) and integration into the country’s health system (63.5%). A majority (93.3%) of the orthopedic surgeons reported having received patients from TBS, and each surgeon had received, on average, 37 patients per year. All the orthopedic surgeons surveyed believed that TBS lacked knowledge in the management of bone injuries, apart from setting bones. Other issues considered critical by the doctors in the management of fractures by TBS included lack of training in the biology of bones (86.7%) and inability to refer cases to modern health facilities (73.3%). The proportion of orthopedic surgeons who had ever thought of a possible interaction between TBS and orthopedic surgeons was 80.0% while 86.7% would advise the establishment of such interaction. Furthermore, the study reveals that more than half (54.6%) of TBS patients made a TBS clinic their first choice for treatment. The paper concludes that integration will go a long way to improving the health of the population, thereby significantly reducing deaths or disability-adjusted life years (DALYs) lost.
End-to-End Deep Learning CT Image Reconstruction for Metal Artifact Reduction

Metal artifacts are common in CT-guided interventions due to the presence of metallic instruments. These artifacts often obscure clinically relevant structures, which can complicate the intervention. In this work, we present a deep learning CT reconstruction called iCTU-Net for the reduction of metal artifacts. The network emulates the filtering and back projection steps of the classical filtered back projection (FBP). A U-Net is used as post-processing to refine the back projected image. The reconstruction is trained end-to-end, i.e., the inputs of the iCTU-Net are sinograms and the outputs are reconstructed images. The network does not require a predefined back projection operator or the exact X-ray beam geometry. Supervised training is performed on simulated interventional data of the abdomen. For projection data exhibiting severe artifacts, the iCTU-Net achieved reconstructions with SSIM = 0.970±0.009 and PSNR = 40.7±1.6. The best reference method, an image based post-processing network, only achieved SSIM = 0.944±0.024 and PSNR = 39.8±1.9. Since the whole reconstruction process is learned, the network was able to fully utilize the raw data, which benefited from the removal of metal artifacts. The proposed method was the only studied method that could eliminate the metal streak artifacts.
Fine Tuning of an Oxidative Stress Model with Sodium Iodate Revealed Protective Effect of NF-κB Inhibition and Sex-Specific Difference in Susceptibility of the Retinal Pigment Epithelium

Oxidative stress of the retinal pigment epithelium (RPE) is a major risk factor for age-related macular degeneration (AMD). As a dry AMD model via oxidative stress, sodium iodate (NaIO3), which is primarily toxic to the RPE, has often been used at a high dose to cause RPE death for studying photoreceptor degeneration. Thus, characterization of RPE damage by a low dose of NaIO3 is still limited. To quantify RPE damage caused by NaIO3 in mice, we recently developed a morphometric method using RPE flat-mounts. Here, we report that NaIO3 has a narrow range of dose–effect correlation at 11–18 mg/kg body weight in male C57BL/6J mice. We evaluated the usefulness of our quantification method in two experimental settings. First, we tested the effect of NF-κB inhibition on NaIO3-induced RPE damage in male C57BL/6J mice. IKKβ inhibitor BAY 651942 suppressed upregulation of NF-κB targets and protected the RPE from oxidative stress. Second, we tested sex-specific differences in NaIO3-induced RPE damage in C57BL/6J mice using a low dose near the threshold. NaIO3 caused more severe RPE damage in female mice than in male mice. These results demonstrate the usefulness of the quantification method and the importance of fine-tuning of the NaIO3 dose. The results also show the therapeutic potential of IKKβ inhibition for oxidative stress-related RPE diseases, and reveal previously-unrecognized sex-specific differences in RPE susceptibility to oxidative stress.
Analysis of Overhead Costs Management in Companies

The development of overhead costs management is becoming more and more important as the percentage of overhead costs is rising. The last 15 years have demonstrated the awakening of advanced methods and tools aimed at understanding the utilization of overheads better. The paper investigates the current state of overhead costs management using a sample of 20 companies in Austria, Hungary, and Slovakia. A qualitative approach was applied in a multi-case study, which unveiled the significance of overhead cost management with the increasing trend of importance. The effort reflects current innovations using digitalization of processes. The findings show that (1) the majority of the companies indicated that digitalization heavily impacts overhead costs; (2) all expressed their dissatisfaction with the tools currently used; and (3) the majority cited that usability and speed are the predominant factors. The analysis and the subsequent synthesis delivered three theses: (1) perception that digital competence enables overhead costs management; (2) belief that competencies are insufficient; and (3) there are prerequisites for success in overhead costs management. The paper examines the situation in seven industries represented in the sectors of manufacturing and transportation/storage for the time period from 2008 to 2017. The paper concludes with several recommendations for academia, businesses, and future research. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Preparation and characterization of magnetorheological fluids by dispersion of carbonyl iron microparticles in PAO/1-octanol

This work reports an investigation into the effect of 1-octanol concentration in the formulation of concentrated polyalphaolefin-based magnetorheological fluids. Special emphasis is paid to the understanding of their kinetic stability and redispersibility characteristics in the ‘off-state’ (absence of magnetic field). Techniques employed involve light scattering, electroacoustics and rheometry, using a vane tool, to precisely determine the yield value. The results obtained show a minimum in the rheological material functions for 1-octanol concentrations within the range 0.5–5.0 wt%. This finding is tentatively explained in terms of the potential energy of interaction between the dispersed particles as a result of the formation of 1-octanol micelles in good agreement with Bombard and Dukhin (2014 Langmuir 30 4517–21).