Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Analysis of Machine Learning Methods for Non-Intrusive Indoor Occupancy Detection and Estimation

Occupancy-driven application research has been active research for a decade that focuses on improving or replacing new building infrastructure to improve building energy efficiency. Existing approaches for HVAC energy saving are putting more emphasis on occupancy detection, estimation, and localization to trade-off between energy consumption and thermal comfort satisfaction. In a non-intrusive approach, various sensors, actuators, and analytic data methods are commonly used to process data from occupant surroundings and trigger appropriate action to achieve the task. However, the performance of the non-intrusive approach reported in the literature is relatively poor due to the lack of quality of dataset used in model training and expropriate choice of machine learning model. This study proposed a non-intrusive approach that to improve the collection and quality of dataset using data pre-processing. The study collected a training dataset using various sensors installed in the building and developed a model using five machine learning models to determine occupant’s presence and estimate their number in the building. The proposed solution is tested in the living room with a prototype system integrated with various sensors designed to obtain occupant surrounding environmental datasets. The model’s prediction results obtained indicate that it is possible for the proposed solution to obtain data, process, and predict the occupant number with high accuracy (73.6 -99.7% using random forest).
Understanding the Influence of Building Loads on Surface Settlement: A Case Study in the Central Business District of Beijing Combining Multi-Source Data

In metropolitan areas, the static load of high-rise buildings may result in uneven settlement, which seriously threatens residents’ living safety. Studying the response relationship between the additional stress of high-rise buildings and foundation settlement plays an important role in ensuring the safe development of metropolitan cities. Firstly, based on Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology, we used 68 descending TerraSAR-X images to obtain the surface settlement in the study area from April 2010 to October 2018, which were validated with leveling benchmark monitoring results. Secondly, we calculated the additional stress of the building loads to quantify its effect on the uneven settlement in the Central Business District (CBD) of Beijing. Finally, two sets of characteristic points were selected to analyze the response relationships between foundation settlement and additional stress generated by building loads. The findings show: (1) The surface settlement rate varied from −145.2 to 24 mm/year in the Beijing Plain. The InSAR results agree well with the monitoring results derived from the leveling benchmark; the Pearson correlation coefficients were 0.98 and 0.95 in 2011–2013 and 2015–2016, respectively. (2) The stress results show that the depth of the influence of the static load of high-rise buildings was 74.9 m underground in the CBD. (3) The spatial distribution pattern of the additional stress is consistent with the foundation settlement. A characteristic point with greater additional stress in the same group has a higher foundation settlement rate. This relationship has also been found between the uneven foundation settlement and additional stress gradients. These findings provide scientific support for mitigating economic losses due to foundation settlement caused by additional stresses derived from building loads.
Restoring or maintaining the vertical mixing of oceanic waters

Currents generated by wind and the interaction of the rotation of the earth and the gravitational pull of the sun and moon give rise to horizontal surface movement of sea water. Two basic mechanisms that drive the vertical mixing of ocean waters are reviewed in this article, the action of marine organisms and the regional differences in temperature and salinity. The latter mechanism is called thermohaline circulation. Upwelling of cold water of polar origin helps to prevent further warming of the surface of the tropical ocean areas. In doing so, it is also resulting in containing the development of more and stronger hurricanes. The cold water from the oceans’ bottom also supplies minerals. For some areas of the tropical oceans there is no significant amount of mineral supply from other sources. Adequate supply of minerals is essential for life on the surface of the oceans. There was a time when marine animals diving deep into the oceans and returning to the surface made mixing of surface water with water deeper down happen supplies the required minerals to the oceans’ surface. However, humanity’s large-scale slaughter of marine creatures, led to decimation of the sea life from the second millennium AD onwards. Before that marine life played an important part in the vertical mixing of the oceans. The focus of this article is, however, on the need to maintain the vertical mixing of ocean water and its relation to the more recent issue of global heating. This is an issue where, it is argued here, a technological remedy is feasible.
Evaluation of a student-centered online one-to-one tutoring system

ABSTRACT This paper introduces a system that supports student-centered online one-to-one tutoring and evaluates the practical value of the system by running an experiment with 64 experienced mathematics teachers and 810 students in Grade 7. The experiment lasted for 50 days. A comprehensive evaluation was performed using students’ academic performance before and after usage of the system and the system log files. By classifying the students into active and inactive usage groups, it was determined that active students significantly outperformed inactive students on posttests, but with a small effect size. The results also suggested that high prior knowledge students tended to benefit more from using the system than low prior knowledge students. An explanation for this result was that students with a high level of prior knowledge were more likely to have good-quality interactions with their teachers. Therefore, although some advantages of this type of student-centered online one-to-one tutoring are observed, in this system, both the students and the teachers need to be further facilitated to produce more effective tutoring interactions.
Hybrid-Light-Source Stereolithography for Fabricating Macro-Objects With Micro-Textures

Microscale surface structures are commonly found on macroscale bodies of natural creatures for their unique functions. However, it is difficult to fabricate such multi-scale geometry with conventional stereolithography processes that rely on either laser or digital micromirror device (DMD). More specifically, the DMD-based mask projection method displays the image of a cross-section of the part on the resin to fabricate the entire layer efficiently; however, its display resolution is limited by the building area. In comparison, the laser-based vector scanning method builds smooth features using a focused laser beam with desired beam-width resolution; however, it has less throughput for its sequential nature. In this paper, we studied the hybrid-light-source stereolithography process that integrates both optical light sources to facilitate the fabrication of macro-objects with microscale surface structures (called micro-textures in the paper). The hardware system uses a novel calibration approach that ensures pixel-level dimensional accuracy across the two light sources. The software system enables designing the distribution and density of specific microscale textures on a macro-object by generating projection images and laser toolpaths for the two integrated light sources. Several test cases were fabricated to demonstrate the capability of the developed process. A large fabrication area (76.8 mm × 80.0 mm) with 50 μm micro-features can be achieved with a high throughput.
Discovering the arrow of time in machine learning

: Machine learning (ML) is increasingly useful as data grow in volume and accessibility. ML can perform tasks (e.g., categorisation, decision making, anomaly detection, etc.) through experience and without explicit instruction, even when the data are too vast, complex, highly variable, full of errors to be analysed in other ways. Thus, ML is great for natural language, images, or other complex and messy data available in large and growing volumes. Selecting ML models for tasks depends on many factors as they vary in supervision needed, tolerable error levels, and ability to account for order or temporal context, among many other things. Importantly, ML methods for tasks that use explicitly ordered or time-dependent data struggle with errors or data asymmetry. Most data are (implicitly) ordered or time-dependent, potentially allowing a hidden ‘arrow of time’ to affect ML performance on non-temporal tasks. This research explores the interaction of ML and implicit order using two ML models to automatically classify (a non-temporal task) tweets (temporal data) under conditions that balance volume and complexity of data. Results show that performance was affected, suggesting that researchers should carefully consider time when matching appropriate ML models to tasks, even when time is only implicitly included.
Evaluation and Characteristic of Modified Ventilator Under Hyperbaric Conditions During Volume-controlled Ventilation

Purpose：The stability of the modified ventilator (Shangrila590, Beijing Aeonmed Company, Beijing, China) was evaluated under hyperbaric conditions during volume-controlled ventilation in this study by Michigan test lung (5601i, Grand Rapids, MI, US). Methods：Experiments were performed inside the multiplace hyperbaric chamber at 1.0, 1.5 and 2.0 atmospheres absolute (ATA). The modified ventilator placed inside the hyperbaric chamber was connected to the test lung. During volume-controlled ventilation (VCV), data for the test lung were collected by a personal computer outside the hyperbaric chamber. The preset tide volume (VTset) of the ventilator (400-1000 ml) and the resistance and compliance of the testing lung were adjusted before the experiments at every ambient pressure. With every test setting, the tide volume (VT), inspiratory airway peak pressure (Ppeak) and minute volume (MV) displayed by the ventilator and the test lung were recorded by the computer. We compared the ventilator and test lung data under 1.0, 1.5 and 2.0 ATA to evaluate the stability of the modified ventilator.Results：The variation in VT in the test lung and the ventilator at different ambient pressures changed within a narrow range, and the differences were statistically significant. In every test setting, changes in the MV of the ventilator were limited and acceptable, with significant differences at different ambient pressures. However, Ppeak increased obviously, as detected by the ventilator and test lung at higher ambient pressure during VCV.Conclusions：The modified Shangrila590 ventilator can work well in a hyperbaric chamber. It can provide relatively stable VT and MV during VCV with VTset from 400 ml to 1000 ml when the ambient pressure increases from 1.0 ATA to 2.0 ATA. The raised ambient pressure will lead to increased gas density, which may result in more airway resistance and higher Ppeak during VCV.
A Smart Algorithm for Optimizing Bandpass Filter in Phase Volume Measurement with Off-axis Quantitative Phase Imaging

The advantages of measuring the volume of a phase object through off-axis quantitative phase imaging include fast acquisition rate, great temporal stability, and high spatial phase sensitivity. However, the accuracy of a measured volume is limited by the different noises of measurement system and finite bandpass filter applied in the phase-extraction algorithm. To improve the accuracy of the volume measurement, it has been recommended to apply an appropriate bandpass filter in the procedure of phase retrieval. An optimum size of bandpass filter can provide better accuracy by passing sample phase information and blocking unwanted noises. The present study introduce a smart method which can provide optimum bandpass filter for each object so that the accuracy of phase volume measurement increases as much as possible. Different type of windows is studied in the phase retrieval procedure and by comparing the results, the Gaussian window function is suggested to be utilized in the smart algorithm. Finally, the feasibility of the method is proved by applying the smart algorithm on our previous experiment results related to quantitative phase imaging on a bead, an optical fiber, and a spherical mirror. The results obtained by the smart algorithm method are in good agreement with the optimum filter obtained by testing different filter sizes.
Energy-Based Motion Control for Pneumatic Artificial Muscle Actuated Robots With Experiments

The pneumatic artificial muscle (PAM) is a kind of flexible actuators used to simulate the characteristics of human muscles. Robots actuated by PAMs possess compliance and safety, which can achieve satisfactory man–machine interaction control. Nevertheless, such robots actuated by PAMs tend to have lots of control problems due to the inherent characteristics, such as hysteresis, creep, high nonlinearities, and so on, which is not conducive to accurate modeling and motion control. Moreover, most existing control methods do not consider constraining overshoots, etc.; however, based on safety requirements and actual physical constraints, systems with unconstrained overshoots may have potential risks. In this article, a new energy-based nonlinear control method is proposed for 2-link PAM-actuated robots to realize accurate positioning control. For this purpose, first, the dynamic model of 2-link PAM-actuated robots is presented. Further, a new energy storage function is constructed. Additionally, the overshoots and the terms coupled with control inputs are also constrained reasonably, which can reduce the unnecessary energy loss while improving the system safety. To the best of our knowledge, the proposed method is the first nonlinear control approach for 2-link PAM-actuated robots which is designed and analyzed based upon the original nonlinear dynamics without any linearization to provide high-performance positioning control with constrained overshoots and eliminated residual oscillations simultaneously. By rigorous analysis, the asymptotic stability of the system is proven. To validate the effectiveness of the proposed method, a series of hardware experimental results are presented based on a self-built 2-link PAM-actuated robot.
Subclinical hypothyroidism in community perspective: Treat or not to treat?

Subclinical hypothyroidism is a common clinical entity prevalent in the community setting, thyroid hormone testing is one of the most frequently asked investigations, and it also is placed in most health panel tests. It is defined as the value of thyroid-stimulating hormone between 4.5-10mIU/L and normal fT4 and fT3. In community-based studies, the prevalence of subclinical hypothyroidism was observed by nearly 4.4% in males and 7.5–8.5% in females. Prevalence of sub clinical hypothyroidism increases in females with advancing age. There is a gray zone for treating the clinical condition with a TSH value between 4.5-10 mIU/ml. Treatment for subclinical hypothyroidism is also under debate for more than two decades with varying opinions. The main focus of treatment is aimed at one of the following criteria: correction of lipid abnormality, progression to overt hypothyroidism, pregnancy, and other medical conditions. There are different schools of thought for deciding to treat such persons. This review highlights the importance, risk, and benefits of treating such conditions with thyroxin replacement from a community perspective.insufficient data on subclinical hypothyroidism forced medical professionals to screen identified cases and initiate treatment of such conditions in the primary health care setting.We retrieved the relevant literature from PubMed, Medline, and Embase using keywords adult, pregnancy, female, children, adolescent, thyroxine, thyrotropin, TSH, thyroid function test, prevalence, risk factors, hypothyroidism, cardiovascular system, lipids, sub-clinical, primary health care, community.
Opportunities to reduce nitrous oxide emissions from horticultural production systems in Canada

Abstract: Horticultural systems, specifically vegetable production systems, are considered intensive agricultural systems as they are characterized by high nitrogen (N) fertilizer application rate, frequent tillage, and irrigation operations. Accordingly, horticultural production in temperate climates is prone to N losses — mainly during post-harvest (during fall and winter) or pre-plant (spring) periods — such as N2O emissions and nitrate leaching. The risk for N losses is linked to low crop N use efficiency (NUE) combined with a narrow C:N and high N content of crop residues. Here we reviewed the studies conducted in Canada and similar climates to better understand the risk of N2O emission and potential agronomic management strategies to reduce N2O emissions from horticultural systems. Current knowledge on N2O emissions from horticultural systems indicate that increasing crop NUE, modifying the amount, type, time, and rate of N fertilizer inputs, and adopting cover crops in crop rotations are some of the effective approaches to decrease N2O emissions. However, there is uncertainty related to the efficiency of the existing N2O mitigation strategies due to the complex interactions between the factors (soil characteristics, type of plant species, climatic conditions, and soil microbial activity) responsible for N2O production from soil. Little research on N2O emissions from Canadian horticultural systems limits our ability to understand and manage the soil N2O production processes to mitigate the risk of N2O emissions. Thus, continuing to expand this line of research will help to advance the sustainability of Canadian horticultural cropping systems.
Las colecciones botánicas como fuente de enseñanza: el caso FES-Cuautitlán, UNAM

knowledge, perception and expectations generated by scientific collections as vectors for learning basic botany. The results indicate that the Botanical Garden is the most visited, while the FESC Herbarium is little frequented; however, the latter is the most widely used collection in Agricultural Engineering career, where most students consider the use of scientific collections to be beneficial in their academic development. The biological collections preserved in the FES-Cuautitlan, both the Herbarium and the Botanical Garden, fully comply with research, scientific dissemination, and teaching tasks, particularly this last task is key for the correct learning of the students.
Biogeographic drivers of distribution and abundance in an alien ecosystem engineer: Transboundary range expansion, barriers to spread, and spatial structure

Biogeographic boundaries can act as either weak or strong barriers to the spread of species undergoing distributional change. Once a novel species spreads across a boundary, it can have a substantial impact on the ecosystem, for instance by competing with local species, and, over the long‐term, re‐engineer the ecosystem. Marine biogeographic regions are clearly defined on the coast of southern Africa and we tested the influence of their boundaries on the spread and spatial structure of an alien ecosystem engineer.
An 8-nation empirical test of three interpersonal listening techniques

ABSTRACT Listening is a fundamental element of good marketing. Marketing relies on clear, effective, interactive communication: between the firm and customers, between the firm and suppliers, and within the firm among employees. While prior research has emphasized the crucial importance of good listening skills to individual and organizational performance, only a few listening techniques have been assessed empirically, particularly under difficult listening circumstances. This paper fills that gap in the literature by building on prior conceptual and exploratory work on listening, identifying 3 listening techniques, and empirically testing the effectiveness of the techniques using a multinational sample. Results show that listening techniques improve recall, but the most effective technique depends on the countries’ level of individualism.
To what extent do political parties utilize similar frames?

How parties compete by utilizing frames in the public debate is not well understood. A widespread understanding is that parties tend to compete by talking past each other, i.e. when they utilize dissimilar frames. This article relies on a unique data set of parties’ framing of four individual policy questions over two decades in Denmark to examine frame overlap, i.e. when parties adopt similar frames. Results show that parties utilize similar and dissimilar frames in the public debate. However, a high degree of frame similarity was generally found across parliamentary blocs (between the leading mainstream party from each bloc, their leading junior coalition partner, and the two blocs) and most often a very high degree of overlap was found within parliamentary blocs (between the leading mainstream party and its junior coalition partner). This result suggests a need to rethink thoroughly how to understand and study interaction among parties utilizing frames.
Characteristics of Indoor Flood Fatalities: Evidence from Greece

Despite the important advances in flood forecasting and protection, floods remain one of the most lethal types of natural hazards. Previous works have explored several factors influencing the risks of flooding to human life and health. However, there is limited research and understanding on indoor flood fatalities and the circumstances under which they occur. This study explores victim-, building-, and situation-related characteristics in order to provide a better understanding of the conditions that lead to flood-related indoor deaths, exploiting a fatality database developed for Greece (1960–2020). The correlation analysis showed that indoor victims, compared with outdoor ones, tend to be older individuals, with high percentages of disabilities. A significant statistical association of the building material, roof type, and distance from the river with the building collapse was also found. The profile of the buildings in which flood fatality occurred was further compared with that of neighboring non-fatal buildings that were inhabited during the flood events. The statistical results indicated that the buildings with a fatality occurrence are mostly single-storey structures, made from masonry as the main building material. The findings have practical implications in risk communication and mitigation in terms of identifying the specific populations, circumstances, settings, and mechanisms that lead to dangerous indoor situations during flooding events.
The Econometrics of Early Childhood Human Capital and Investments

This article reviews recent developments in the econometrics of early childhood human capital and investments. We start with a discussion about the lack of cardinality in test scores, the reasons it matters for empirical research on human capital, and the approaches researchers have used to address this problem. Next, we discuss how the literature has accounted for the errors in human capital measurements and investments. Then, we focus on the estimation of production functions of human capital. We present two different specifications of the production function and discuss when to use one versus the other. We describe how researchers have addressed cardinality, measurement errors, and endogeneity of inputs to estimate the technology of skill formation. Finally, we take stock of the work to date, and we identify opportunities for new research directions in this field.