Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Deep-Learning-Based Robust Data Transmission Period Control Framework in IoT Edge Computing System

This article proposes a novel deep learning-based robust Internet of Things (IoT) sensor data transmission period control (DL-RDTPC) framework in an IoT edge computing system. In general, as the data transmission period of IoT sensors increases, the energy consumption of IoT sensors is reduced, and contrarily, the amount of un-transmitted data (i.e., missing values) becomes continuously accumulated. Therefore, the IoT server is in charge of accurately imputing these missing data for reliable data analysis. By addressing this issue, we newly design the imputation accuracy prediction (IAP) module, which captures the complicated relationships between the imputation accuracy and the data transmission period, in order to estimate the imputation accuracy, precisely. For constructing the IAP, three submodules, which include a stacked bidirectional long short-term memory (Bi-LSTM) model, a multihead convolutional neural network (CNN), and a neural network-based period information encoding network (PIEN) are leveraged. To balance the tradeoff between the imputation accuracy and energy consumption regarding the data transmission period, the multiobjective optimization problem is formulated for minimizing the maximum value of both: 1) the energy consumption of IoT sensors obtained from the analytical model and 2) the imputation accuracy predicted from IAP module. The optimal solution is consequently obtained by utilizing the bisection search algorithm. Extensive performance evaluations validate the effectiveness of the proposed RDTPC algorithm in terms of both the average energy consumption (maximum 68% reduction) and missing data imputation accuracy (maximum 64% RMSE reduction) over other benchmarks. Finally, this article provides a practical implementation of the proposed RDTPC framework via the HTTP protocol under the IEEE 802.11-based WLAN network, as well as interworking with the commercial cloud server.
Sequential Semantic Segmentation of Road Profiles for Path and Speed Planning

Driving video is available from in-car camera for road detection and collision avoidance. However, consecutive video frames in a large volume have redundant scene coverage during vehicle motion, which hampers real-time perception in autonomous driving. This work utilizes compact road profiles (RP) and motion profiles (MP) to identify path regions and dynamic objects, which drastically reduces video data to a lower dimension and increases sensing rate. To avoid collision in a close range and navigate a vehicle in middle and far ranges, several RP/MPs are scanned continuously from different depths for vehicle path planning. We train deep network to implement semantic segmentation of RP in the spatial-temporal domain, in which we further propose a temporally shifting memory for online testing. It sequentially segments every incoming line without latency by referring to a temporal window. In streaming-mode, our method generates real-time output of road, roadsides, vehicles, pedestrians, etc. at discrete depths for path planning and speed control. We have experimented our method on naturalistic driving videos under various weather and illumination conditions. It reached the highest efficiency with the least amount of data.
The Increase in Children’s Math Skill from an Experimental Increase in Parent Investment in Math Activities

Almost none of the research showing that greater parent engagement increases children’s cognitive skill exogenously increases parent engagement. In a randomized experiment we find that providing parents with information and materials relevant to engaging in math activities along with text messages to reduce present bias increased both parents’ engagement in math activities and children’s math skill. But a separate treatement that provided families with an electronic tablet and math apps that required no parent engagmenet increased math skill by at least as much. Data Replication Statement: The data used in this article are available online: Kalil, Ariel, and Mayer, Susan. MPACT Fall 2017 Fall 2018 Chicago. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-07-27. https://doi.org/10.3886/E176341V1 Disclosure Statement: The authors gratefully acknowledge financial support from The Heising-Simons Foundation in San Francisco, CA, The Overdeck Family Foundation in New York, NY, The Paul M. Angell Family Foundation in Chicago, IL, and The Robert R. McCormick Foundation in Chicago, IL. The authors have received no significant financial support from an other individual, group, or organization outside of these named sponsors to complete this research. None of the authors or their relatives or partners hold positions with any organization whose policy positions, goals, or financial interests relate to this work. No other party outside of the authors and acknowledged research staff members have had the right to review this paper prior to its submission. IRB approval has been obtained for this research (IRB16-0880, University of Chicago Social & Behavioral Sciences IRB). JEL Codes: I24, I26, I29
Black Soldier Fly (Hermetia illucens) as a Potential Agent of Organic Waste Bioconversion

The use of black soldier fly (BSF) as a bioconversion agent has become an emerging breakthrough in waste processing. Organic wastes, such as household waste and livestock manure, can be used as a growth medium for BSF larvae and converted into favorable products. The average composting time of BSF larvae is around 12– 15 days, which is faster than that of microbes or earthworms (4–5 weeks). BSF shows potential as a feed and food ingredient because it has a high nutritional content, such as enzyme, chitin, medium-chain fatty acid, and antimicrobial peptides, and can be used as a functional food ingredient. From an economical perspective, the short composting period and the role of BSF as a feed and food alternatives can benefit producers and consumers. The safety aspects of BSF utilization, including microbial safety, chemical safety, and environmental safety, warrant clarification to ensure BSF safety. However, some challenges arise regarding the use of BSF larvae (BSFL) as a bioconversion agent, such as for heavy metal residues, pesticide residues, pathogens, and antimicrobial gene transmission and residues that require the best composting strategy for mitigation. The environmental safety of organic waste treated with BSFL has a good impact; therefore, this strategy can be used to reduce global warming. Research must focus on effectively and safely enhancing the cultivation and processing of BSF and its applications as a functional food. In conclusion, BSF is a profitable alternative for organic waste bioconversion in developed and developing countries.
İşletmelerde Finansal Olmayan Performans Değerleme Yaklaşımları: Kavramsal Bir Çerçeve

Performance appraisal approaches, which are constantly changing and developing in enterprises from the past to the present, are very important for decisions to be taken for the future. In performance evaluation approaches, the data obtained by financial measurements provide information about performance. Financial measurements are financial indicators that consist of accounting records and are of interest to shareholders and managers. With the change in the economic environment, practitioners and academics have criticized financial valuations for having short-term, retrospective and summary information, and have concluded that new performance valuation approaches should be applied in changing market and competition conditions. Many of the enterprises have also started using non-financial performance appraisal approaches that will provide effective, efficient and customer satisfaction to eliminate the limitations of financial performance measurements in the last two decades. With the change of customer demands and market competition conditions, enterprises have demonstrated an innovative attitude with non-financial performance evaluation approaches in their decision-making processes. In the transition from the traditional management approach to the modern management approach, customer satisfaction, employee satisfaction, superior quality, innovation, etc. approaches that give weight to the issues are applied. Elements such as design, purpose, cost, selection and qualities of performance enhancement need to be done in a realistic way. In this study, non-financial performance evaluation approaches (Benchmarking, Enterprise Resource Planning, Outsourcing, Six Sigma, Customer Relationship Management, Reengineering, Total Quality Management) have been investigated in a conceptual framework, a performance appraisal approach and successful in the market it was concluded that advantage can be achieved.
Enhanced Performance of Single-Walled Carbon Nanotube-Germanium Near-Infrared Photodetector by Doping with Au Nanoparticles

This paper presents a near-infrared (near-IR) photodetector based on a gold nanoparticles-doped (AuNPs-doped), single-walled carbon nanotube–germanium (SWCNT/Ge) heterojunction. The responsivity, detectivity, and response time of the AuNPs-doped, SWCNT/Ge heterojunction photodetector measured 476 mA W−1 (a 291% improvement), 1.0 × 1012 cm Hz1/2 W−1 (a 208% improvement), and 8 μs, respectively. The mechanism of the enhanced performance originated from the surface modification by gold doping, which effectively improved the work function of the carbon nanotube films and thus increased the barrier height between the heterojunctions, as measured by the contact potential distribution (CPD) and open circuit voltage (Voc) of the SWCNT/Ge interface. In addition, we investigated the effect of various particle sizes on the performance and stability of the photodetector. The results demonstrate the promising prospects of the presented heterojunction photodetector for infrared detection applications.
The Perturbation of the B1Π and C1Σ+ States in KLi

Abstract Polarization labelling spectroscopy of the B1Π←X1Σ+ and C1Σ+←X1Σ+ band systems in KLi reveals strong mutual perturbation of the B and C states. We show that both excited states can be described in a model comprising numerical IPA potentials for the unperturbed states and only 3 parameters to describe their interaction. Our approach allows to identify many previously unassigned spectral lines having significant deviation from the “regular” positions.
A review of different ventilation methods for controlling the transmission of the virus during the COVID-19 pandemic

With the COVID-19 pandemic sweeping worldwide, much attention has been paid to infectious viruses. Because of the different sizes of pathogen-carrying droplets exhaled by individuals infected with COVID-19, the influence of gravity and inertia on the droplets varies, which leads to different modes of transmission of the virus. Ventilation changes the air distribution in a room, and affects virus transmission. An appropriate ventilation method that reduces the floating time of viruses and the exposure rate of the human body should be selected. Although previous studies have extensively reviewed methods to reduce the airborne transmission of viruses, research on ventilation methods remain limited. This review aimed to explore a ventilation mode that could ensure the thermal comfort and maintain low exposure and infection rates in the human body. This study investigated the transmission modes of the virus and the importance of particle size. The effects of mixing ventilation, displacement ventilation, impinging jet ventilation, and stratum ventilation on the removal of different particle sizes and applications at various locations were compared. The results of this study can contribute to reducing the indoor virus concentrations during the COVID-19 pandemic.
A Critical Look at Ice Crystal Growth Data

I review published data relating to the growth of ice crystals from water vapor under various conditions, and I critically examine the different measurements to determine what useful information can be extracted from each. I show that most, and possibly all, of the existing growth data have been seriously distorted by systematic errors of one form or another, to varying degrees. Many data sets are dominated by systematic effects, so that the conclusions drawn from them are unreliable. I list and describe these systematic errors in some detail so that they may be avoided in future experiments. I then cautiously draw conclusions from the growth data and compare with theories pertaining to our current understanding of the crystal growth dynamics of ice.
Species, taxonomic, and functional group diversities of terrestrial mammals at risk under climate change and land‐use/cover change scenarios in Mexico

There is a need to revise the framework used to project species risks under climate change (CC) and land‐use/cover change (LUCC) scenarios. We built a CC risk index using the latest Intergovernmental Panel on Climate Change framework, where risk is a function of vulnerability (sensitivity and adaptive capacity), exposure, and hazard. We incorporated future LUCC scenarios as part of the exposure component. We combined a trait‐based approach based on biological characteristics of species with a correlative approach based on ecological niche modeling, assigning risk scores to species, taxonomic (orders), and functional (trophic, body size, and locomotion) groups of terrestrial mammals occurring in Mexico. We identified 15 species projected to lose their climatic suitability. Of the 11 taxonomic orders, Eulipotyphla, Didelphimorphia, Artiodactyla, and Lagomorpha had the highest risk scores. Of the 19 trophic groups, piscivores, insectivores under canopy, frugivores–granivores, herbivores browser, and myrmecophagous had the highest risk scores. Of the five body‐sized groups, large‐sized species (>15 kg) had highest risk scores. Of the seven locomotion groups, arboreal and semi‐aquatics had highest risk scores. CC and LUCC scenarios reduced suitable areas of species potential distributions by 37.5% (with CC), and 51% (with CC and LUCC) under a limited full‐dispersal assumption. Reductions in suitable areas of species potential distributions increased to 50.2% (with CC), and 52.4% (with CC and LUCC) under a non‐dispersal assumption. Species‐rich areas (>75% species) projected 36% (with CC) and 57% (with CC and LUCC) reductions in suitability for 2070. Shifts in climatic suitability projections of species‐rich areas increased in number of species in northeast and southeast Mexico and decreased in northwest and southern Mexico, suggesting important species turnover. High‐risk projections under future CC and LUCC scenarios for species, taxonomic, and functional group diversities, and species‐rich areas of terrestrial mammals highlight trends in different impacts on biodiversity and ecosystem function.
Neutrinos in Cosmology and Particle Physics

This thesis discusses two independent research topics. We first study keV sterile neutrinos as a Warm Dark Matter (WDM) candidate, focusing on their production at temperatures of the electroweak scale and the linear structure growth of WDM particles with arbitrary distribution functions and masses of keV scale. At temperatures of the electroweak scale, the medium effect modifies the mixing angle between sterile and active neutrinos, introducing two narrow Mikheev-Smirnov-Wolfenstein (MSW) resonances that break adiabaticity and enhance the non-thermal production of sterile neutrinos at small momenta. One of the two MSW resonances is in the absence of a lepton asymmetry and occurs only at temperatures around the electroweak scale. By solving the linearized collision-less Boltzmann equation, we obtain a semi-analytical expression of the matter power spectrum for WDM particles with arbitrary distributions agreeing within a few percent error with results from Boltzmann codes. This matter power spectrum depends on the horizon size at matter-radiation equality and the free streaming wave vector kfs, function of mass and distribution of WDM particles. We discover WDM acoustic oscillations at small scales about k>=2k_fs and an Integrated Sachs-Wolfe (ISW) effect in the Radiation Dominant (RD) era which enhances the matter power spectrum for k<=k_fs. A quasi-degeneracy between the mass and distribution function of WDM on the matter power spectrum is identified, suggesting an inherent ambiguity of Lyman-alpha analysis to constrain WDM parameters. Secondly, based on the observation that neutrinos produced from decay via the charge current interaction are entangled with the corresponding charged leptons, we re-investigate the theory of neutrino oscillations with the focus of the dynamics of the entangled state. We study the dynamics of entanglement and dis-entanglement explicitly in time, which leads to non-conventional expressions for neutrino oscillation amplitudes and probabilities suggesting possible corrections for short baseline neutrino oscillation experiments. By applying this method to the GSI anomaly, we unambiguously show that the GSI anomaly is not a consequence of neutrino oscillations.
Infinite horizon optimal control : deterministic and stochastic systems

This book presents a systematic account of the development of optimal control problems defined on an unbounded time interval - beginning primarily with the work of the early seventies to the present. The first five to six chapters provide an introduction to infinite horizon control theory and require only a minimal knowledge of mathematical control theory. The remainder of the book considers extensions of the previous chapters to a variety of control systems, including distributed parameter systems, stochastic control systems and hereditary systems. Throughout the book it is possible to distinguish three categories of research: the extension of the classical necessary conditions to various weaker types of optimality (eg, overtaking optimality); the discussion of various sufficient conditions and verification theorems for the various types of optimality and the discussion of existence theorems for the various types of optimality. The common link between these categories is the "turnpike property" and the notion of "reduction to finite costs". Once these properties are established for a given control system, it is possible to begin investigating the issues described in the above three categories. This monograph on economics, mathematics, systems engineering and operations research is intended for researchers.
Strain-engineered graphene through a nanostructured substrate. II. Pseudomagnetic fields

The strain induced pseudo-magnetic field in supported graphene deposited on top of a nanostructured substrate is investigated by using atomistic simulations. Step, elongated trench, one dimensional barrier, spherical bubbles, Gaussian bump and Gaussian depression are considered as support structures for graphene. From the obtained optimum configurations we found very strong induced pseudo-magnetic fields which can reach up to $\sim$ 1000\,T due to the strain-induced deformations in the supported graphene. Different magnetic confinements with controllable geometries are found by tuning the pattern of the substrate. The resulting induced magnetic fields for graphene on top of a step, barrier and trench are calculated. In contrast to the step and trench the middle part of graphene on top of a barrier has zero pseudo-magnetic field. This study provides a theoretical background for designing magnetic structures in graphene by nanostructuring substrates. We found that altering the radial symmetry of the deformation, changes the six-fold symmetry of the induced pseudo-magnetic field.
Dinosaur tracks in the Dakota Formation (Aptian-Albian) at Clayton Lake State Park, Union County, New Mexico

Every fall since 1950, the New Mexico Geological Society (NMGS) has held an annual Fall Field Conference that explores some region of New Mexico (or surrounding states). Always well attended, these conferences provide a guidebook to participants. Besides detailed road logs, the guidebooks contain many well written, edited, and peer-reviewed geoscience papers. These books have set the national standard for geologic guidebooks and are an essential geologic reference for anyone working in or around New Mexico.
Upsampling method for sparse light detection and ranging using coregistered panoramic images

Abstract. We present a method to upsample low-resolution light detection and ranging (LiDAR) data using coregistered panoramic images collected in urban environments. The context is a mobile mapping vehicle equipped with a LiDAR scanner and spherical camera system, where the goal is to recover a three-dimensional model of the built environment. What makes this problem challenging is that as LiDAR samples become sparse, interpolation becomes difficult as connectivity between points can become ambiguous. The idea behind this paper is to use structural context and information in the associated panoramic images to determine the location of surfaces in the scene, and by inference, the surface membership of the LiDAR samples. With the latter determined, surfaces can then be reconstructed via interpolation using a function appropriate to the task at hand. We show that this method is effective in recovering details that are not apparent in the initial dataset. In the event that images are either uninformative or not available, we introduce a fallback method for surface segmentation that infers depth discontinuities from the properties of the surface triangulation. Experimental results are presented showing the performance of both methods on data acquired from an urban setting.
Does the Narrow [O III] λ5007 Line Reflect the Stellar Velocity Dispersion in Active Galactic Nuclei?

It has been proposed that the width of the narrow [O III] λ5007 emission line can be used as a surrogate for the stellar velocity dispersion in active galaxies. This proposition is tested using the Sloan Digital Sky Survey (SDSS) Early Data Release (EDR) spectra of 107 low-redshift radio-quiet QSOs and Seyfert 1 galaxies by investigating the correlation between black hole mass, as determined from Hβ FWHM and optical luminosity, and [O III] FWHM. The correlation is real, but the scatter is large. Without additional information or selection criteria, the [O III] width can predict the black hole mass to a factor of 5.
Combinatorial remarks on two-dimensional Languages

La these contient une premiere chapitre avec des preliminaires sur les langages bidimensionnels, nous donnons un bref examen des resultats principaux et des differentes caracterisations des langages reconnaissables par de systeme de Tiling System, qui jouent le role central dans la these. Alors nous decrivons la structure algebrique des familles des langages locales. Nous prouvons que cette structure est un treillis en ce qui concerne l'inclusion et nous etudions les proprietes du treillis. D'ailleurs nous traitons des problemes informatiques, etudiant leur possibilite de decision et nous donnons la position, dans la hierarchie arithmetique, des problemes classiques sur des langages unidimensionnels maintenant tournees aux langues bidimensionnels. Dans la these apres quelques definitions du basic au sujet de polyominoes, nous traitons le recognizability de plusieurs classes de polyominoes par des langues reconnaissables par de Tiling System. En particulier nous donnons les Tiling systemes de pour des langues representant quelques classes de polyominoes convex, comme H-convex ou parallelogramme. D'ailleurs nous etudions la recognizability de L-convex polyominoes. En conclusion, la piece d'essai de la these est consacree a l'application des langages reconnaissables par de Tiling systemes au calcul d'ADN. Nous donnons l'idee au sujet de la construction avec de l'ADN de quelques classes de polyominoes (c. -a-d. La classe de parallelogramme polyominoes), obtenons a travers la famille des langues reconnaissables par de Tiling systemes.