Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Group Multi-Criteria Approach Based on SAW, TOPSIS, VIKOR, and COPRAS Methods for Complex IoT Selection Problems

The growth of Internet of Things (IoT) systems is driven by their potential to improve efficiency, enhance decision-making, and create new business opportunities across various domains. In this paper, the main selection problems in IoT-type systems, criteria used in multi-criteria evaluation, and multi-criteria methods used for solving IoT selection problems are identified. Then, a Hybrid Group Multi-Criteria Approach for solving selection problems in IoT-type systems is proposed. The approach contains the Best Worst Method (BWM) weighting method, multi-criteria Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Complex Proportional Assessment Method (COPRAS), and a method that combines the solutions obtained using the four considered multi-criteria methods to obtain a single solution. The SAW, TOPSIS, VIKOR, and COPRAS methods were analyzed in relation to their advantages, disadvantages, inputs, outputs, measurement scale, type of normalization, aggregation method, parameters, complexity of implementation, and interactivity. An application of the Hybrid Group Multi-Criteria Approach for IoT platform selection and a comparison between the SAW, TOPSIS, VIKOR, and COPRAS solutions and the solution of the proposed approach is realized. A Spearman correlation analysis is presented.
Experimental Investigation of the Topographic Modification of Earthquake Ground Motion

Experimental Investigation of the Topographic Modification of Earthquake Ground Motion Jacob Dafni Chair of the Supervisory Committee: Chair Joseph Wartman Civil and Environmental Engineering Topographic modification of earthquake ground motion can significantly impact ground motion amplitude and frequency content. While previous studies have investigated topographic modification of ground motion, also called “topographic effect”, there are discrepancies between the results of field and numerical investigations. A new experimental approach involving physical modeling in a geotechnical centrifuge was used to study topographic effects. The centrifuge captures the complexity of a physical process and shares many of the advantages of a numerical model (e.g., material properties, instrumentation location, and ground motions can be controlled). Experimental results show that topographic amplification can exceed amplification due to subsurface geology (i.e., “site amplification”). The results also indicate the main cause of topographic amplification is slope resonance, which leads to differential movement, and the development of shear planes between the slope and surrounding landmass. Slope resonant frequencies are within the range considered in engineering practice, which can impact the design of structures near slopes. Findings from the centrifuge investigation were used to inform analyses of a ridge in the Port Hills suburb of Christchurch, New Zealand. Topographic effects were analyzed using data from a downhole array located adjacent to two cliff faces. A simplified procedure was adopted to establish a reference free field station. Results of the analyses were found to be in good agreement with the centrifuge investigation.
A review of methods for measuring groundwater–surface water exchange in braided rivers

Abstract. Braided rivers, while uncommon internationally, are significant in terms of their unique ecosystems and as vital freshwater resources at locations where they occur. With an increasing awareness of the connected nature of surface water and groundwater, there have been many studies examining groundwater–surface water exchange in various types of waterbodies, but significantly less research has been conducted in braided rivers. Thus, there is currently limited understanding of how characteristics unique to braided rivers, such as channel shifting, expanding and narrowing margins, and a high degree of heterogeneity affect groundwater–surface water flow paths. This article provides an overview of characteristics specific to braided rivers, including a map showing the regions where braided rivers are mainly found at the global scale: Alaska, Canada, the Japanese and European Alps, the Himalayas, Russia, and New Zealand. To the authors' knowledge, this is the first map of its kind. This is followed by a review of prior studies that have investigated groundwater–surface water interactions in braided rivers and their associated aquifers. The various methods used to characterise these processes are discussed with emphasis on their effectiveness in achieving the studies' objectives and their applicability in braided rivers. We also discuss additional methods that appear promising to apply in braided river settings. The aim is to provide guidance on methodologies most suitable for future work in braided rivers. In many cases, previous studies found a multi-method approach useful to produce more robust results and compare data collected at various scales. Given the challenges of working directly in braided rivers, there is considerable scope for the increased use of remote sensing techniques. There is also opportunity for new approaches to modelling braided rivers using integrated techniques that incorporate the complex river bed terrain and geomorphology of braided rivers explicitly. We also identify a critical need to improve the conceptual understanding of hyporheic exchange in braided rivers, rates of recharge to and from braided rivers, and historical patterns of dry and low-flow periods in these rivers.
Push&Pull: autonomous deployment of mobile sensors for a complete coverage

Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push&Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push&Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.
Dynamics of Water Soil Storage in the Unsaturated Zone of a Sand Dune in a Semi-Arid Region Traced by Humidity and Carbon Isotopes: The Case of Ashdod, Israel

ABSTRACT A 22 m sediment core was collected from the unsaturated zone (USZ) in the dunes south of Ashdod, Israel, in a low rainfall year, following an even lower-rainfall year. The mineralogy of was quartz with some clay and carbonate. The local climate is semi-arid. The roots of the sparse vegetation can reach ~8 m. The porosity was ~40–55%. The DIC ranged from 2 to 13 mmole C/L. Large variability is noted in the soil moisture, with a maximum at the high clay region at ~8 m. Oxygen isotopes enter the USZ with rain falling on the surface. There is 18O enrichment in the top of the section due to evaporation during the summer. Below this depth δ18O values of ~ –5‰ prevail as in the local aquifer. CO2 and the carbon isotopes enter the USZ laterally by exhalation from roots. The δ13C varies from –5‰ to –23‰, representing stages in carbon isotopic fractionation: CO2gas becomes dissolved CO2aqueous which then forms carbonic acid and HCO3 – . The high δ13C, Δ14C, and DIC are found at the 8 m depth. These values along with high humidity are replicated at ~22m depth. They most probably represent recharge water from the previous rainy season at 8 m depth subsequently pushed down 12.8±0.8 m during the last winter.
Indoor scene texturing based on single mobile phone images and 3D model fusion

ABSTRACT Realistic texture mapping and coherent up-to-date rendering is one of the most important issues in indoor 3-D modelling. However, existing texturing approaches are usually performed manually during the modelling process, and cannot accommodate changes in indoor environments occurring after the model was created, resulting in out-dated and misleading texture rendering. In this study, a structured learning-based texture mapping method is proposed for automatic mapping a single still photo from a mobile phone onto an already-constructed indoor 3-D model. The up-to-date texture is captured using a smart phone, and the indoor structural layout is extracted by incorporating per-pixel segmentation in the FCN algorithm and the line constraints into a structured learning algorithm. This enables real-time texture mapping according to parts of the model, based on the structural layout. Furthermore, the rough camera pose is estimated by pedestrian dead reckoning (PDR) and map information to determine where to map the texture. The experimental results presented in this paper demonstrate that our approach can achieve accurate fusion of 3-D triangular meshes with 2-D single images, achieving low-cost and automatic indoor texture updating. Based on this fusion approach, users can have a better experience in virtual indoor3-D applications.
Artiﬁcial Intelligence in Medicine

Objective: Clinical documents reﬂect a patient’s health status in terms of observations and contain objec-tive information such as descriptions of examination results, diagnoses and interventions. To evaluate this information properly, assessing positive or negative clinical outcomes or judging the impact of a medical condition on patient’s well being are essential. Although methods of sentiment analysis have been developed to address these tasks, they have not yet found broad application in the medical domain. Methods and material: In this work, we characterize the facets of sentiment in the medical sphere and identify potential use cases. Through a literature review, we summarize the state of the art in health-care settings. To determine the linguistic peculiarities of sentiment in medical texts and to collect open research questions of sentiment analysis in medicine, we perform a quantitative assessment with respect to word usage and sentiment distribution of a dataset of clinical narratives and medical social media derived from six different sources. Results: Word usage in clinical narratives differs from that in medical social media: Nouns predominate. Even though adjectives are also frequently used, they mainly describe body locations. Between 12% and 15% of sentiment terms are determined in medical social media datasets when applying existing sentiment lexicons. In contrast, in clinical narratives only between 5% and 11% opinionated terms were identiﬁed. This proves the less subjective use of language in clinical narratives, requiring adaptations to existing methods for sentiment analysis. Conclusions: Medical sentiment concerns the patient’s health status, medical conditions and treatment. Its analysis and extraction from texts has multiple applications, even for clinical narratives that remained so far unconsidered. Given the varying usage and meanings of terms, sentiment analysis from medical documents requires a domain-speciﬁc sentiment source and complementary context-dependent features to be able to correctly interpret the implicit sentiment.
Storm time coupling between the magnetosheath and the polar ionosphere

The present study demonstrates the feasibility of using plasma and magnetic field data from Defense Meteorological Satellite Program (DMSP) satellites to estimate the Alfvénic reflectances (α) in the polar cap ionosphere during periods of geomagnetic disturbance. Quantitative values of α are then used to support calculations of field‐aligned Poynting flux (S||i) transmitted along open field lines from magnetosheath generators to the conjugate polar ionospheres. Analyzed data were acquired during high‐latitude passes of DMSP F16 during the 17 March 2013 magnetic storm. Between the main phase onset and the day's end, plasma velocity and magnetic field perturbations manifest the phase relations predicted by Alfvén and Fälthammar (1963) for electromagnetic coupling. The most reliable (sunward‐antisunward) components of measured plasma velocities and magnetic perturbations are consistent with that α ranging between 0.65 and 0.97, with a mean of ~0.8. Subsequent calculations indicate that incident S||i varied between 0.2 and 0.02 W/m2 with a mean of 0.085. We suggest that these reported ranges of α and S||i reflect both large variations in IMF BZ and the growth of antisunward neutral winds in the polar caps during the storm's main phase.
The Impact of Personalized versus Standardized Cardiorespiratory and Muscular Training on Health-Related Outcomes and Rate of Responders.

Recent research has shown more favorable training adaptations for inactive adults when cardiorespiratory fitness (CRF) exercise is prescribed with the use of ventilatory thresholds compared to percentages of heart rate reserve (HRR). However, there is limited research on changes in health-related outcomes with the use of these CRF methods in combination with muscular fitness exercises. The objective of this study was to compare the effectiveness of two training programs for improving CRF, muscular fitness, and cardiometabolic risk factors. Inactive men and women (n=109, aged 49.3±15.5 years) were randomized to a non-exercise control group or one of two exercise training groups. The exercise training groups consisted of 13 weeks of structured exercise with progression using either CRF exercise prescribed with the use of ventilatory thresholds and functional training for muscular fitness (THRESH group) or HRR and traditional muscular fitness training (STND group). After the 13-week protocol, there were significant differences in body weight, body composition, systolic blood pressure, high-density lipoprotein cholesterol (HDL-c), VO2max, 5-repetition maximum (RM) bench press, and 5-RM leg press for both treatment groups compared to the control group after controlling for baseline values. However, the THRESH group had significantly more desirable outcomes for VO2max, 5-RM bench press, 5-RM leg press, body composition, and HDL-c when compared to both the STND and control group. Additionally, the proportion of individuals estimated as likely to respond above 3.5 mL·kg-1·min-1 in VO2max (i.e., the minimal clinically important difference) was 76.4%, 20.8%, and 0.13% for the THRESH, STND, and control groups, respectively. While both exercise programs elicited favorable health-related adaptations after 13 weeks, these results suggest that a personalized program with exercise prescribed based on ventilatory threshold and with the use of functional muscular fitness training may yield greater training adaptations.
Accelerated Continuous Conditional Random Fields for load forecasting

Enabling commercial buildings to use energy in a flexible way, such as reducing usage during consumption peak hours, is of crucial importance, not only for preventing the disruptions of the utility grid, but also for containing buildings' rapidly growing energy cost. Such smart energy consumption, however, heavily relies on accurate short-term energy load forecasting, such as hourly predictions for the next n (n > 2) hours. To attain sufficient accuracy, we treat such multisteps ahead regression task as a sequence labeling (regression) problem, and adopt the Continuous Conditional Random Fields (CCRF) to explicitly model these interconnected outputs. A Predictive Clustering Trees (PCT) is proposed, aiming to divide the relationships of related outputs into a set of “sub-relationships”, each providing more specific feature constraints for the interplays of the related outputs. For the multi-dimensional target space, the PCT partitions the input space, namely X, into different disjoint regions, where each is a leaf and each groups instances with similar values for the target variables Ys. Intuitively, depending on X, the PCT forms sub-relationships among targets, thus enabling the CCRF to better capture the correlations between related outputs.
Importing Inputs for Climate Change Mitigation: The Case of Agricultural Productivity

This paper estimates agricultural total factor productivity (TFP) in 162 countries between 1991 and 2015 and aims to understand sources of cross-country variations in agricultural TFP levels and its growth rates. Two factors affecting agricultural TFP are analyzed in detail – imported intermediate inputs and climate. We first show that these two factors are independently important in explaining agricultural TFP – imported inputs raise agricultural TFP; and higher temperatures and rainfall shortages impede TFP growth, particularly in low-income countries (LICs). We also provide a new evidence that, within LICs, those with a higher import component of intermediate inputs seem to be more shielded from the negative impacts of weather shocks.
Could Having Access to Real-Time Data on Your Emotions Influence Subsequent Behavior? Evidence from a Randomized Controlled Trial of Japanese Office Workers

Improvements in mental health through real-time feedback on emotions have consequences for productivity and employee wellness. However, we find few extant studies on how real-time feedback on emotions can influence subsequent behavior modification in the Japanese workplace. We conducted a randomized controlled trial (RCT) with 30 employees of an insurance company in Japan and observed their emotions for 10 working days using a wearable biometric device. We compared the emotions of employees who had access to real-time emotional states (treatment group) with those of employees who did not (control group). The results of the panel regression analysis showed that access to real-time emotions was negatively associated with happy emotions and positively associated with angry and sad emotions. The results indicated that even after having access to the objective statuses of emotions, participants were unable to continue with happy emotions and reverse angry and sad emotions to other comfortable emotions. Our findings imply that feedback on real-time emotional states should be associated with appropriate training and motivation to utilize feedback for behavioral modification.
Type 1 diabetes mellitus, hyperlipidemia, and inflammatory bowel disease: a Mendelian randomization study

Previous epidemiologic studies have shown a close association between type 1 diabetes mellitus (T1DM), hyperlipidemia, and inflammatory bowel disease (IBD), but the causal relationship has not been established. In the current study the causal relationships between T1DM and hyperlipidemia with IBD were assessed using Mendelian randomization (MR) analysis. A two-sample MR study was conducted utilizing accessible genome-wide association study data from public sources with the selection of suitable instrumental variables adhering to the principles of MR analysis. The primary technique utilized was the inverse variance weighted method, complemented by additional methods, such as MR-Egger regression, weighted median, simple mode, weighted mode, and the MR pleiotropy residual sum and outlier approach. Genetically determined T1DM had no causal relationship with IBD or IBD subtypes based on MR analysis. These findings were consistent across all supplementary methods used. In addition, genetically determined hyperlipidemia had no causal relationship with IBD or IBD subtypes, even after increasing the number of instrumental variables used. Our study supports the notion that there is no causal relationship between T1DM and IBD, as well as hyperlipidemia and IBD, which contradicts most observational studies.
Processing of organic contaminants by large lakes: impacts and fates

A challenge facing investigators oflarge lakes, such as the Laurentian Great Lakes of North America, is understanding the impacts of pollurants on these ecosystems and developing models for predicting the transport, cycling and fate of pollutants. Persistent organic pollutants are of particular concern. Many physical, chemical and biological processes comrol the fate of pollutants once they have been emitted into the environment, and research efforts have focused on describing these processes. Parricular attention has been paid to the biologically mediared processes of bioaccumulation and benthic recycling.
Millimeter Wave Antennas: A State-of-the-Art Survey of Recent Developments, Principles, and Applications

: The increasing volumes of data generated by social networking, cloud computing, e-commerce, and online video broad-casting necessitate the implementation of higher data rates. As the current 4G network encounters congestion and potentially struggles to accommodate the substantial data demand, there is a growing interest in millimeter wave (mmWave) technology. The 30–300GHz mmWave spectrum is characterized by its broad bandwidth and low latency; it is having many applications in communication domains, also includes 5G cellular. Despite its atmospheric attenuation and non-line-of-sight (NLOS) propagation, the majority of nations have begun to implement mmWave 5G in the band of 28/38GHz as a result of its reduced path loss exponent, minimal signal spread, and decreased atmospheric attenuation. While the patch antenna (single-element) is a compact and easily transportable choice for mmWave applications, its radiation efficiency, gain, and bandwidth are all subpar. Array antennas have effectively addressed these limitations by exhibiting significant enhancements in bandwidth, gain, and radiation efficiency. It is still limited in the maximum data rates it can accommodate. The rate of data can be increased by a factor of one thousand using Multiple-Input-Multiple-Output (MIMO) technology, which is enabled by geographical diversity and multiplexing techniques. As a result, the comprehension of structures of MIMO antennas operating at mmWave is imperative for the continued enhancement of performance. In comparing the efficacy of these designs, bandwidth, isolation, efficiency, gain, and radiation pattern are considered. In this paper, the most recent planar MIMO antenna designs, which are categorized as defected ground structures, Slot/Patch/Stub, MIMO Antenna Array, Dielectric Resonator Antenna, and Meta-Surface/Metamaterial Structures, are described. This paper also addresses the effects that slots, partial ground, and decoupling structures have on levels of isolation, bandwidth, and impedance matching. A comprehensive analysis of the design considerations and subsequent advancements is also provided in this paper.