Miracle-dz/UniFAR-FTUs huggingface dataset:
Longitudinal distributions of dicarboxylic acids, ω‐oxoacids, pyruvic acid, α‐dicarbonyls, and fatty acids in the marine aerosols from the central Pacific including equatorial upwelling

Remote marine aerosol samples (total suspended particles) were collected during a cruise in the central Pacific from Japan to Mexico (1°59′N–35°N and 171°54′E–90°58′W). The aerosol samples were analyzed for dicarboxylic acids (C2–C11), ω‐oxoacids, pyruvic acid, α‐dicarbonyls, and fatty acids as well as organic and elemental carbon, water‐soluble organic carbon, and total nitrogen (WSTN). During the study, diacids were the most abundant compound class followed by fatty acids, ω‐oxoacids, and α‐dicarbonyls. Molecular compositions of diacids showed a predominance of oxalic (C2) acid followed by malonic (C3) and succinic (C4) acids. Oxalic acid comprises 74% of total diacids. This result suggests that photochemical production of oxalic acid is significant over the central Pacific. Spatial distributions of diacids, ω‐oxoacids, pyruvic acid, α‐dicarbonyls, and fatty acids together with total carbon and WSTN showed higher abundances in the eastern equatorial Pacific where the upwelling of high‐nutrient waters followed by high biological productivity is common, indicating that their in situ production is important in the warmer central Pacific through photochemical oxidation from their gaseous and particulate precursors. This study demonstrates that there is a strong linkage in biogeochemical cycles of carbon in the sea‐air interface via ocean upwelling, phytoplankton productivity, sea‐to‐air emissions of organic matter, and formation of secondary organic aerosols in the eastern equatorial Pacific.
A Case Study for a Hybrid Model of Behavior Modification

Schools have an obligation to maintain a safe and orderly learning environment. Additionally, schools have an obligation to foster productive behaviors in their students that will mitigate for the need to suspend students. In an effort to reduce student suspensions, many schools and school systems are turning to P ositive B ehavioral I ntervention S ystems (PBIS) for solutions. The full paper provides a case study for an alternative discipline strategy that provides teachers with greater autonomy while reducing the need to monitor individual student behavior.
Performance Evaluation of Epileptic Seizure Prediction Using Time, Frequency, and Time–Frequency Domain Measures

The prediction of epileptic seizures is crucial to aid patients in gaining early warning and taking effective intervention. Several features have been explored to predict the onset via electroencephalography signals, which are typically non-stationary, dynamic, and varying from person-to-person. In the former literature, features applied in the classification have shared similar contributions to all patients. Therefore, in this paper, we analyze the impact of the specific combination of feature and channel from time, frequency, and time–frequency domains on prediction performance of disparate patients. Based on the minimal-redundancy-maximal-relevance criterion, the proposed framework uses a sequential forward selection approach to individually find the optimal features and channels. Trained models could discriminate the pre-ictal and inter-ictal electroencephalography with a sensitivity of 90.2% and a false prediction rate of 0.096/h. We also present the comparison between the classification accuracy obtained by the optimal features, several features summarized from optimal features, and the complete set of features from three domains. The results indicate that various patient interpretations have a certain specificity in the selection of feature-channel. Furthermore, the detailed list of optimal features and summarized features are proffered for reference to those who research the corresponding database.
A Distribution Method of Driving Torque for a Novel 3UPS-RR Redundant Solar Tracker

This paper proposes a novel two-axis solar tracker with a redundant parallel mechanism and investigates the distribution method of driving torque. In view of the difference between the singular configuration of the redundant parallel mechanisms and that of the corresponding non-redundant ones, an index related to the minimum singular value of the Jacobian matrix is used to indicate the position of the singular configuration relative to the boundaries of the required workspace. The driving torque and energy consumption can be optimized with this index. Based on the fact that the direction of driving torque is opposite to that of rotor in most of the running processes, a distribution method of driving torque with the minimum energy consumption for the redundant parallel solar tracker is proposed. The distribution method is compared with the minimum norm solution which is adopted by the conventional redundant parallel mechanism. And energy consumption can be significantly reduced by adopting this method. In addition, the workspace and energy consumption of the redundant solar tracker and its non-redundant counterpart are compared. The results show that the redundant solar tracker has a larger workspace and lower energy consumption.
Measurement of moisture content using time domain reflectometry during the biodrying of sewage sludge with high electrical conductivity

ABSTRACT Measurements of real-time moisture content by time domain reflectometry (TDR) is a prospective method which can be used in the sewage sludge biodrying. This study was conducted to investigate the impact of high electrical conductivity on moisture measurement and realize the application in sewage sludge with high conductivity. TDR waveforms were analyzed and the probe was optimized. Measurement by standard probe was possible when the conductivity was lower than 3 mS cm−1, and only coated probe could be used when the conductivity increased to 15.04 mS cm−1. Calibration equations were developed with R2 values above 0.990.
Filmmaking as a source of enhanced knowledge and transformation in conflicts over small-scale fisheries: the case of Colombia

Small-scale fisheries (SSF) harvesting on coastal and inland aquatic ecosystems sustain the livelihood of hundreds of millions around the world. In Colombia, as in many other developing countries, SSF suffer from multiple pressures and conflicts. Yet the research on SSF conflicts is scarce and the typology of these conflicts is poorly systematized and understood. Existing studies lack the necessary interdisciplinary integration to address social-ecological processes involved in SSF. Moreover, scientific research requires building trust with fishers in order to gain an accurate picture of relevant intra-community processes and values. In face of this situation, we compiled information from nonfiction films about fishing conflicts, with the double aim of underpinning scientific knowledge on conflicts over SSF and analyzing the use of the films to promote transformations in these conflicts. Our empirical evidence relies on the organization of an ad hoc docu-conference where filmmakers, fishers, and the general public engaged in a meaningful discussion on the issues affecting SSF communities in Colombia. Films represent the range of conflicts over SSF in 31 locations of 16 Colombian departments and provide data about types of actors involved in the conflicts, types of conflicts and their causes, and possible courses of action. We gained insights into fishing conflicts as processes of change that involve drivers and impacts with common patterns in both inland waters, and marine and coastal environments but evolve in diverging responses or calls for action. Beyond the variables emerging in the films, audiovisual content supports stakeholders in their pursuit of knowledge sharing, political mobilization, and social functioning. Films about SSF conflicts expand knowledge and relatedness that propel intellectual processes tending to exacerbate the conflict and/ or stimulate sense of place, enhance governance, and give a boost to alternatives. Research participants (filmmakers, fishers, and the public) discussed advantages and limitations of using films to tackle the SSF crisis in Colombia. We demonstrate the value of films in social-ecological research and provide evidence of how they can support and bring about transformative change.
Fenton’s Oxidation of Personal Care Product (PCP) Wastewater: A Kinetic Study and the Effects of System Parameters

Personal care products (PCPs) are considered an emerging class of pollutants, and PCP wastewater is classified as hazardous because it contains organic compounds, which are linked to high chemical oxygen demand (COD) concentrations. PCP wastewater is dangerous when discharged into rivers without treatment, which entails oxidizing complex organic compounds into simpler compounds using advanced oxidation technology (AOT). Fenton’s reagent is composed of Fe 2+ and H 2 O 2 and can oxidize organic compounds, thus reducing COD concentrations. This study aims to determine the effectiveness of the AOT method by calculating COD removal in wastewater; analyze the effect of the Fe 2+ /H 2 O 2 ratio, H 2 O 2 concentration, and system pH; develop a kinetics model of COD reduction; and analyze the cost of PCP wastewater treatment. The parameters used in the study are Fe 2+ /H 2 O 2 ratio, H 2 O 2 concentration, and pH. The results of this study show that the highest level of COD removal was 88.59% at a Fe 2+ /H 2 O 2 ratio of 9% w/w, a H 2 O 2 concentration of six times the COD concentration, and a pH value of 3. The reaction followed pseudo-first-order reaction kinetics, and the reaction rate constant was 0.021 min − 1 . At a flow rate of 15 m 3 /day, which is applicable in an industrial site, the required reactor volume in a continuous system is less than that for a batch system. The required reactor volume for a plug flow reactor and a batch reactor are 1.625 m 3 and 2.25 m 3 , respectively. The estimated cost to treat 1 liter of wastewater is IDR 1,385.
Time-Spatial Features of Mix El Niño

The diversity of El Niño is a critical field of the climate research. The eastern Pacific (EP) and central Pacific (CP) types of El Niño have been identified in the previous studies. However, the extreme El Niño event that occurred in 2015–2016 is quite different from both the EP and CP El Niño events. The sea surface temperatures anomalies (SSTA) for this event widely spread in both the central and eastern Pacific and have a small zonal gradient in the central-eastern Pacific. Many researchers regarded this event as a mixed type of El Niño. Using the regression-EOF method, the Mix El Niño pattern is extracted from the tropical Pacific SSTA field during the period from 1900 to 2019. Here, we reveal that the Mix El Niño is a very usual rather than a new type of El Niño, it is just that the EP and CP El Niño events are more frequent since the 1980s, while the Mix El Niño events frequently appear before the 1980s. The time-spatial features of the Mix El Niño are further investigated. The results demonstrate a unique westward propagation of the maximum SSTA for the Mix El Niño from the far eastern Pacific to the central Pacific. In contrast, the SSTA center is locked in the far eastern Pacific region for the EP El Niño and the central Pacific region for the CP El Niño. The evolutions of subsurface ocean temperature anomalies and sea surface height anomalies are also examined to support this. The ocean–atmosphere interaction plays an important role in the evolution of the Mix El Niño. The anomalous atmospheric Walker circulation for the Mix El Niño is mainly in the western and central Pacific as well as very weak in the eastern Pacific. In contrast, there are significant westerlies/easterlies in the eastern Pacific for the EP/CP El Niño. The small gradient of SSTA in the central-eastern Pacific for the Mix El Niño leads to weak zonal wind anomalies, which further weaken the zonal gradient of SSTA. All this suggests that the Mix El Niño is not unusual and fundamentally different from the EP and CP El Niño with important implications for global climate effects.
Adaptive event-triggered fault detection for Markovian jump systems with network time-delays

In this paper, the adaptive event-triggered fault detection (FD) problem is investigated for Markovian jump systems (MJSs) with network time-delays and data package dropouts. First, a novel event-triggered communication strategy with an adaptive threshold is introduced to screen the sampled signals and reduce the data releasing frequency. Consequently, the limited communication resources and network bandwidth are saved as much as possible. Second, since communication links between the plant and filter are considered to be unreliable, the effects of intermittent package dropouts phenomenon and network time-delays are taken into account simultaneously. By using time-delay system method, the network-induced phenomena, adaptive event-triggered strategy and MJSs are unified into a networked MJSs time-delay system. Then, sufficient conditions are developed such that the resulting residual system is mean-square exponentially stable with the desired H ∞ performance. Finally, a numerical example of the F-404 aircraft engine system is provided to illustrate the effectiveness and potential of the proposed design method.
Personal Carbon Trading—Lost in the Policy Primeval Soup?

The number of emission trading and carbon taxation schemes implemented has grown rapidly over the past decade. Together, they cover approximately 16% of global greenhouse gas (GHG) emissions. Although more than two-thirds of global GHG emissions are related to household consumption, approaches that directly target households, such as personal carbon trading (PCT), do not play a role in the fight against climate change. This is especially puzzling as measures taken so far are not sufficient to reach the 2 °C target. One clue to solving this puzzle comes from political science in the form of the multiple streams approach, which defines criteria that a policy proposal must meet to become part of the political agenda. Based on these criteria, this article conducts a systematic review on PCT to clarify why PCT does not play a role in the reduction of GHG emissions. The results show that there are three main problems with the PCT proposal. First, scholars often criticize the set-up costs as well as the running costs of such a system. Second, there is no clear consensus within the research community on public acceptance of PCT. Third, it is still unclear whether politicians are receptive to PCT or not.
Efficient multi-way sparsity estimation for hyperspectral image processing

Abstract. Sparsity and low rankness are essential properties of real-world data. The sparsity attribute mentions that the data contain very few non-zero elements. On the other hand, the low-rank property characterizes redundancy in the data. The concept of sparsity and low rankness is central to numerous signal processing tasks such as signal inversion, data compression, and noise removal. With the advent of multi-sensor and multi-dimensional data, we frequently encounter multi-way data or tensors with sparse and low-rank structure. Prevalent vector or matrix-based sparsity estimation criterias cannot conveniently characterize the sparsity structure of multi-way data. Hence, we require efficient criteria to quantify the sparsity structure of multi-way data. Sparsity plays a crucial aspect in hyperspectral image processing tasks such as unmixing and denoising. Hyperspectral images contain an inherent multi-way structure; we perform multi-way sparsity estimation in hyperspectral image processing. We introduce an efficient criterion to estimate multi-way sparsity, facilitating signal inversion, and noise removal tasks. The proposed sparsity criteria combine the sparsity of the core tensor obtained by Tucker tensor decomposition, the low rankness of the tensor, and the approximated rank. Since the core tensor obtained by tucker decomposition is highly sparse, the core tensor sparsity reflects the sparsity of the whole tensor indirectly. On the other hand, the nuclear norm and Stein’s unbiased risk estimate quantifies the low rankness of the tensor. Unlike other approaches, our proposed measure takes both low rankness and sparsity attribute into account. In addition, our proposed sparsity measure also satisfies some of the desirable properties of ideal sparsity measures. We demonstrate the efficacy of our proposed sparsity quantification measure in applications such as hyperspectral image denoising, hyperspectral unmixing tasks as demonstrated in the real image experiments.
Identification and Analysis of Strawberries’ Consumer Opinions on Twitter for Marketing Purposes

Data are currently characterized as the world’s most valuable resource and agriculture is responding to this global trend. The challenge in that particular field of study is to create a Digital Agriculture that help the agri-food sector grow in a fair, competitive environment. As automated machine learning techniques and big data are global research trends in agronomy, this paper aims at comparing different marketing techniques based on Content Analysis to determine the feasibility of using Twitter to design marketing strategies and to determine which techniques are more effective, in particular, for the strawberry industry. A total of 2249 hashtags were subjected to Content Analysis using the Word-count technique, Grounded Theory Method (GTM), and Network Analysis (NA). Findings confirm the results of previous studies regarding Twitter’s potential as a useful source of information due to its lower execution and analysis costs. In general, NA is more effective, cheaper, and faster for Content Analysis than that based both on GTM and automated Word-count. This paper reveals the potential of strawberry-related Twitter data for conducting berry consumer studies, useful in increasing the competitiveness of the berry sector and filling an important gap in the literature by providing guidance on the challenge of data science in agronomy.
Inquiry-Based Learning Approaches to Enhance Engagement among Post Graduate Students in Research Methodology Courses

Lecturers teaching research methodology courses often feel concerned when discovering many students attempted research without the necessary research methodology skills even after completed compulsory faculty-organized research methodology (RM) courses. The lack of research knowledge and skills is evident when the submitted research proposal deemed not robust enough to qualify for a feasible study. Scholars identify lack of deep learning during RM courses as the main factor since the courses are perceived as not having context and uninteresting hence there was little engagement with the material. Inquiry-based Reflectice Learning (IBL) has been argued to effectively rectify this as its pedagogies involve students in discovery learning that uses activities that are regulated by students. IBL requires students to apply questioning and researching skills to explore, conduct analysis, communicate, and reflect on information. In the study, inquiry-based instruction was used to encourage students to develop multiple perspectives and encourages empathy with the subject and eventually enhance engagement. The study involves a reflective cases study of research methodology courses to explore the lecturer’s classroom practice using IBL and the students’ experiences participating in IBL activities. st. The methodology used involve conducting a needs analysis via Google Form survey, interviewing and document analysis of the lecturers’ teaching plans and field notes and the reflections by both the lecturers and students. The findings from the survey indicate that most students admit they have minimal research skills and require assistance particularly practical research skills. Data from the reflections and field notes also show that students feel engaged with discovery activities conducted, while the lecturer feel students understand better and more engaged with IBL activities conducted. The study has shed significant input on the needs of RM students, participants’ experiences, and the challenges of implementing RM course using IBL. Some recommendations to facilitate more deep learning experiences among postgraduate students taking RM courses are also proposed.
Characterization of Ash-Forming Matter in Various Solid Fuels by Selective Leaching and Its Implications for Fluidized-Bed Combustion

This paper presents the results of standard fuel analyses of 112 different fuels, along with the results from chemical fractionation through selective leaching. The samples, obtained from boilers during the period 1995–2010, represent the following fuel classes: coal, peat, wood-derived fuels, agricultural wastes, and sewage sludge. The leaching results show that coal consists mainly of insoluble ash forming matter, dominated by different silicates. The ash-forming matter in wood-derived fuels is mainly soluble and is dominated by potassium, calcium, and phosphorus; the insoluble ash-forming matter originates from soil contamination. The ash-forming matter in peat has the characteristics of both wood-derived fuels and coal. In agricultural waste, the ash-forming matter is mainly soluble, even though it may contain some silicon, and is dominated by potassium, chlorine, and phosphorus. The ash-forming matter in sludge is mainly acid-soluble or insoluble. It is also important to note that the aluminum silica.
International retrospective natural history study of LMNA-related congenital muscular dystrophy

Abstract Muscular dystrophies due to heterozygous pathogenic variants in LMNA gene cover a broad spectrum of clinical presentations and severity with an age of onset ranging from the neonatal period to adulthood. The natural history of these conditions is not well defined, particularly in patients with congenital or early onset who arguably present with the highest disease burden. Thus the definition of natural history endpoints along with clinically revelant outcome measures is essential to establishing both clinical care planning and clinical trial readiness for this patient group. We designed a large international cross-sectional retrospective natural history study of patients with genetically proven muscle laminopathy who presented with symptoms before two years of age intending to identify and characterize an optimal clinical trial cohort with pertinent motor, cardiac and respiratory endpoints. Quantitative statistics were used to evaluate associations between LMNA variants and distinct clinical events. The study included 151 patients (median age at symptom onset 0.9 years, range: 0.0–2.0). Age of onset and age of death were significantly lower in patients who never acquired independent ambulation compared to patients who achieved independent ambulation. Most of the patients acquired independent ambulation (n = 101, 66.9%), and subsequently lost this ability (n = 86; 85%). The age of ambulation acquisition (median: 1.2 years, range: 0.8–4.0) and age of ambulation loss (median: 7 years, range: 1.2–38.0) were significantly associated with the age of the first respiratory interventions and the first cardiac symptoms. Respiratory and gastrointestinal interventions occurred during first decade while cardiac interventions occurred later. Genotype–phenotype analysis showed that the most common mutation, p.Arg249Trp (20%), was significantly associated with a more severe disease course. This retrospective natural history study of early onset LMNA-related muscular dystrophy confirms the progressive nature of the disorder, initially involving motor symptoms prior to onset of other symptoms (respiratory, orthopaedic, cardiac and gastrointestinal). The study also identifies subgroups of patients with a range of long-term outcomes. Ambulatory status was an important mean of stratification along with the presence or absence of the p.Arg249Trp mutation. These categorizations will be important for future clinical trial cohorts. Finally, this study furthers our understanding of the progression of early onset LMNA-related muscular dystrophy and provides important insights into the anticipatory care needs of LMNA-related respiratory and cardiac manifestations.