Miracle-dz/UniFAR-FTUs huggingface dataset:
An Effective Very Short-Term Wind Speed Prediction Approach Using Multiple Regression Models

As one of the dominant forms of renewable energy sources, wind power generation plays an increasingly important role in modern energy landscape. A very short-term wind speed prediction is essential for monitoring and control of power systems with high wind power penetration to improve system stability and reliability. In this article, an accurate five-minute horizon wind speed prediction method is proposed by integrating and comparing four machine learning regression algorithms, including multiple-layer perception regressor (MLPR), random forest regressor (RFR), K-nearest neighbors regressor (KNNR), and decision tree regressor (DTR). Twenty minutes historical data of wind speed in a one-minute interval is used for wind speed predictions, which are actual wind speed data provided by the National Renewable Energy Laboratory (NREL), Golden, CO, USA. The proposed method is intended to offer an effective and low-cost way for very short-term wind speed prediction. Pearson’s correlation coefficient (PCC) is adopted for feature selection. The four algorithms are evaluated through statistic error indices and Bland–Altman method, and the MLPR algorithm shows the best performance.
The Signaling Pathways and Targets of Natural Compounds from Traditional Chinese Medicine in Treating Ischemic Stroke

Ischemic stroke (IS) is a common neurological disorder associated with high disability rates and mortality rates. At present, recombinant tissue plasminogen activator (r-tPA) is the only US(FDA)-approved drug for IS. However, due to the narrow therapeutic window and risk of intracerebral hemorrhage, r-tPA is currently used in less than 5% of stroke patients. Natural compounds have been widely used in the treatment of IS in China and have a wide range of therapeutic effects on IS by regulating multiple targets and signaling pathways. The keywords “ischemia stroke, traditional Chinese Medicine, Chinese herbal medicine, natural compounds” were used to search the relevant literature in PubMed and other databases over the past five years. The results showed that JAK/STAT, NF-κB, MAPK, Notch, Nrf2, and PI3K/Akt are the key pathways, and SIRT1, MMP9, TLR4, HIF-α are the key targets for the natural compounds from traditional Chinese medicine in treating IS. This study aims to update and summarize the signaling pathways and targets of natural compounds in the treatment of IS, and provide a base of information for the future development of effective treatments for IS.
Gaussian free fields and Riemannian rigidity

In the present paper, we show that on a compact Riemannian manifold ( M, g ) of dimension d 6 4, the renormalized partition function Z g ( λ ) of a massive Gaussian Free Field determines the Laplace spectrum of ( M, g ) hence imposes some strong geometric constraints on the Riemannian structure of ( M, g ). In any ﬁnite dimensional family of Riemannian metrics of negative sectional curvature bounded from below and above and whose isometry group is trivial, there is only a ﬁnite number of isometry classes of metrics with given partition function Z g ( λ ). When d < 4, the same result holds true if the random variable R M : φ 2 : dv has given probability distribution and without the lower bound on the sectional curvatures.
Structure‐based discovery of Licoflavone B and Ginkgetin targeting c‐Myc G‐quadruplex to suppress c‐Myc transcription and myeloma growth

G‐quadruplex (G4), present in the c‐Myc promoter, has emerged as an attractive cancer‐specific molecular target for drug development. So, the discovery of small molecules to stabilize c‐Myc‐G4 to inhibit transcription of c‐Myc protein is of great significance. Herein, a combined molecular docking‐based virtual screening strategy, molecular dynamics (MD) simulation, and molecular mechanics/generalized Born surface area (MM/GBSA) free energy calculation was conducted on the existing L6000 Natural Compound Library. Four natural compounds, including Licoflavone B, Demethyleneberberine, Ginkgetin, and Mulberroside C, were predicted to have preferable binding affinities to c‐Myc G4 and then selected for commercial purchase and experimental evaluation. Compounds Licoflavone B and Ginkgetin can significantly inhibit myeloma cell proliferation, with IC50 values <8 μM against the RPMI‐8226 cell line. Moreover, our data demonstrated that the two compounds could simultaneously downregulate c‐Myc transcription and expression. Collectively, compounds Licoflavone B and Ginkgetin might be regarded as new candidates for the development of the more potent c‐Myc‐G4 stabilizers in the future.
Structural Modeling of TRPA1 Ion Channel—Determination of the Binding Site for Antagonists

TRPA1 is a transmembrane cation channel, one of the most promising targets in the context of respiratory diseases. Its general structure has already been experimentally resolved, but the binding site of TRPA1 antagonists such as HC-030031, a model methylxanthine derivative, remains unknown. The present study aimed to determine the potential binding site of xanthine antagonists and to describe their binding mode, using a molecular modeling approach. This study represents the first attempt to bring together site-directed mutagenesis reports and the latest cryo-EM structure of an antagonist bound to TRPA1. Our research suggests that the core moiety of HC-030031 binds to a pocket formed by the TRP-like domain and the pre-S1, S4, S5 helices of one subunit. The structure, determined by cryo-EM, shows interactions of a core hypoxanthine moiety in the same area of the binding site, sharing the interaction of xanthine/hypoxanthine with Trp-711. Moreover, the predicted binding mode of HC-030031 assumes interaction with Asn-855, a residue demonstrated to be important for HC-030031 recognition in site-directed mutagenesis studies. Our model proved to be advantageous in a retrospective virtual screening benchmark; therefore, it will be useful in research on new TRPA1 antagonists among xanthine derivatives and their bioisosteres.
A digital approach to workplace mental health: A randomized
 controlled trial examining the effectiveness of a smartphone-based
 personalized intervention

Objective: This two-arm randomized controlled trial aimed to examine the effectiveness of a smartphone-based online platform which incorporates ecological momentary assessments and ecological momentary interventions with the use of machine learning to reduce psychological distress in working adults. Method: 205 working adults were recruited from a local company. Eligible participants were randomized into either the intervention (n = 106) or the waitlist control condition (n = 99). Participants received 4-week smartphone-based personalised psycho-education sessions and evidence-based exercises related to cognitive behavioural and mindfulness principles, driven by data about emotional state, mood, and feedback after each exercise. Reduction in symptoms of depression, anxiety, and stress, was examined as the primary outcome measure. Results: Significant time (before vs. after intervention) by group (intervention vs. control) interaction effect was found, F (1, 175) = 56.67, p < . 001, η²= . 25. Participants in the intervention group reported less depression, anxiety, and stress symptoms after the intervention (M = 14.38, SD = 15.14) than before the intervention (M = 28.90, SD = 17.99). The attrition rate was 86%. Conclusions: This smartphone-based intervention leveraging both ecological momentary assessments and ecological momentary interventions and employing machine learning was effective in reducing distress in working adults. Findings have informed the next phase of this digital health platform, which will optimize the intervention model via personalization, and contribute to the expanding field of digital mental health.
Critical aggressive acceleration values and models for fuel consumption when starting and driving a passenger car running on LPG

ABSTRACT The models based on vehicle speed have been used to estimate fuel consumption and CO2 emissions. However, these models could not properly estimate the change in fuel consumption and CO2 emissions as the speed changes. As for the alternative method, people try to consider using acceleration instead of speed. Although acceleration has been seriously considered, determining critical aggressive acceleration value in relation to fuel consumption and CO2 emissions is difficult to find. In this study, evaluation models of fuel consumption were developed using instantaneous acceleration, and we defined the critical aggressive acceleration values for different states of the vehicle from the viewpoints of fuel consumption and emissions. We used a mid-sized Liquefied Petroleum Gas (LPG) passenger car and obtained instantaneous data from a digital tachograph installed in the car while it accelerates. We developed two fuel consumption models and found critical aggressive accelerations, respectively: a model of starting vehicle that measures range of speed required to overcome the inertia during acceleration from stop state, and the other model for the driving state. We used Classification and Regression Tree (CART) analysis to find the critical aggressive accelerations at which the increments of fuel consumption change abruptly. As a result, the critical aggressive accelerations causing abrupt change in the increments of fuel consumption were found to be 2.598 m/s2 for the starting of vehicles and 1.4705 m/s2 when driving them. We also found that the increments of fuel consumption can be explained through quadratic and exponential functions with instantaneous acceleration.
Nitrogen- and Halogen-Free Multifunctional Polymer-Directed Fabrication of Aluminum-Rich Hierarchical MFI Zeolites

Aluminum-rich hierarchical MFI-type zeolites with high acidic-site density exhibit excellent activity and selectivity in bulky molecule-involved reactions. However, it is challenging to develop a facile and environmentally benign method for fabricating them. Herein, we employ a polymer that does not contain nitrogen and halogen elements to successfully synthesize aluminum-rich hierarchical ZSM-5 zeolite with a Si/Al ratio of 8 and a significant number of mesopores comprised of oriented-assembled nanocrystals. It is demonstrated that the nitrogen- and halogen-free polymer is instrumental in the formation of the ZSM-5 zeolite by serving as a template for constructing the hierarchical micro/mesoporous structure. Moreover, this polymer also acts as a crystal growth modifier to form a single-crystalline zeolite. Notably, the resultant zeolite shows a better catalytic performance in converting waste plastic into hydrocarbons than a commercial one. Our work enables the synthesis of high-quality hierarchical zeolites without requiring quaternary ammonium templates.
Does Risk Taking Behavior Drive MSME Innovation During Covid-19 Pandemic?

The study will contribute to the understanding of risk-taking behavior effect on the MSMEs innovation since the risk-taking behavior is the tendency of business owners for engaging in decisions that may have the potential to be dangerous to their business, especially for the family business to do some innovations nowadays, in the pandemic Covid-19 era. For the family business, the appropriate level of return that the business owner will obtain compensates their risk-taking behavior. These researchers used samples that consist of 307 MSMEs owners that categorized as the family business in Indonesia as the respondents by distributing online questionnaires. Furthermore, this paper also used control variables, such as the number of family members involved, generation level, founder-CEO duality, and business capital. This study used binary logistic regression for the analytical model. The results show that the business owner's risk-taking behavior, number of family members involved, generation level, founder-CEO duality, and business capital significantly influence MSMEs innovation in Indonesia.
Chemical Properties and Fiber Dimension of Eucalyptus pellita from The 2nd Generation of Progeny Tests in Pelaihari, South Borneo, Indonesia

Eucalyptus pellita F. Muell is one of pulp woods that is being developed through breeding plantation programs in Indonesia. The research aimed at exploring the chemical and morphological characteristics of fiber, and to determine the rank of plus trees from 4 provenances based on the suitability for pulps. The materials included the plus trees of E. pellita (9 years) from the 2nd generation of progeny tests in Pelaihari, South Borneo. Wood properties under investigation included the chemical properties and morphological fiber characteristics (fiber dimensions and its derived properties). In the present study, data were analyzed using descriptive statistic, Analytic Hierarchy Process (AHP) and Pearson`s correlation. Results showed that the chemical properties of E. pellita, i.e. the contents of ethanol-toluene extractives, hot water soluble extractives, holocellulose, alphacelullose, and lignin were , , , , and , respectively. The average values of wood fiber morphology were mm (fiber length), (fiber diameter), of (lumen diameter), (fiber wall thickness), (Runkel ratio), (Luce`s shape factor), (slenderness ratio) and (solids factor). The AHP scoring rank indicated that the best individuals were 28.4. 3.28 (Kiriwo Utara), 12.1. 5.28 (North Kiriwo), 19.11. 5.45 (Serisa Village), 3.8. 4.9 (South Kiriwo), and 6.6. 3.15 (South Kiriwo). Pearson correlation analysis showed significant correlations between the levels of fiber length with alpha-cellulose content (r
ANALISIS PROBABILISTIC MODEL MITIGASI TSUNAMI AKIBAT AKTIVITAS VULKANIK GUNUNG ANAK KRAKATAU DENGAN MENGGUNAKAN DATA PENGINDERAAN JAUH

ABSTRAK Terdapat vector deformasi dari patahan cabang disekitar Sumatran Fault Zone (Sumatera Bagian Selatan-Lampung) sehingga mengakibatkan adanya sesar baru yang terbentuk setelah terjadinya aktifitas vulkanik Gunung Anak Krakatau sejak akhir 2018. Tujuan penelitian ini yaitu melakukan pengamatan aktifitas GAK guna memberikan informasi yang dapat menyatakan bahwa patahan yang terjadi kemungkinan besar disebabkan karena aktifitas vulkanik GAK. Metode yang digunakan yaitu penginderaan jauh dengan memanfaatkan data SAR yang berasal dari sensor PALSAR-2 dan Gambar yang memiliki karakteristik frekuensi L-band di papan dari Advanced Land Observing Satellite (ALOS) dengan sensor gelombang mikro aktif. Hasil yang diperoleh menunjukkan bahwa dengan menggunakan database high-density dari genangan dan informasi run-up, perilaku tsunami lokal dapat dinilai dan dianalisis di daerah tergenang. Adapun data pengukuran ketinggian genangan dan ketinggian run-up akan berguna untuk menyelidiki efektivitas perlindungan tsunami selama kesiapsiagaan risiko bencana. Untuk penelitian lebih lanjut, informasi dinamis tentang tsunami seperti kecepatan atau waktu proses penggenangan diperlukan untuk memahami peristiwa ini.
On the optimized 3D printing and post-processing of PETG materials

Glycol-modified polyethylene terephthalate (PETG) is a reliable middle ground between polylactic acid and acrylonitrile butadiene styrene due to its light weight, impact resistance, toughness, flexibility, and cost-effectiveness. However, during 3D printing, the filament form is prone to oozing and stringing. Herein, we optimized the PETG printability via g-code setting and printing parameter modification, and consideration of filament quality, build plate temperature and leveling, and printing design complexity. Printed PETGs were thermally and chemically annealed, and post-processing conditions including annealing time, temperature, and solvent use were investigated. Mechanical properties were evaluated in terms of print parameter changes and post-processing techniques.
Seaweeds as a Source of Functional Proteins

Protein is one of the major macronutrients essential in human nutrition. Protein sources especially animal sourced proteins are expensive, thus much work has been carried out to explore alternative protein sources. Seaweeds, or macroalgae, are emerging as one of the alternative protein sources. They are rich in protein with an excellent amino acid profile comparable to the other conventional protein sources. Seaweed protein contains bioactive components, such as free amino acids, peptides, lectins, and phycobiliproteins, including phycoerythrin and phycocyanin, among others. Seaweed proteins have been proved for their antihypertensive, antidiabetic, antioxidant, anti-inflammatory, antitumoral, antiviral, antimicrobial, and many other beneficial functional properties. Therefore, seaweed proteins can be a natural alternative source for functional food development. This paper discusses the compositional and nutritional aspects of seaweed protein, protein extraction techniques, functional properties of various seaweed proteins, as well as their safety for new product development and functional food applications.
A fast method for electronic couplings in embedded multichromophoric systems

Electronic couplings are key to understanding exciton delocalization and transport in natural and artificial light harvesting processes. We develop a method to compute couplings in multichromophoric aggregates embedded in complex environments without running expensive quantum chemical calculations. We use a transition charge approximation to represent the quantum mechanical transition densities of the chromophores and an atomistic and polarizable classical model to describe the environment atoms. We extend our framework to estimate transition charges directly from the chromophore geometry, i.e., bypassing completely the quantum mechanical calculations using a regression approach. The method allows to rapidly compute accurate couplings for a large number of geometries along molecular dynamics trajectories.
MATCHING BUILDING LOADS WITH SOLAR AND WIND POWER IN OFFICE OF THE EAEPD AS A MICRO GRID

With the development of distributed generation resources and the increase of energy generation technologies, the operation of power systems faced with new complexities. Using renewable energy resources with small installable capacities at the demand (consumption) side, emplacement is a way to reduce environmental pollution, the use of fossil energy resources and save transport costs. To achieve high penetration depth of renewable sources into the micro-grid, an exact system operation is needed. This paper presents a real micro grid that composed at East Azerbaijan Electric Power Distribution Company (EAEPD). The network is made up a micro grid with distributed energy resources which is connected to the global network. GIS platform is solution for simulate and software for operation of this micro grid. The purpose of model is supplying power to the loads with minimum cost and pollution. The distribution network's required power is provided in two ways: Via the global grid and via small capacity wind turbines and solar panels. Specifically, we focus on network architecture, reliability requirements and challenges of both loads on the building and the resource power supplies.
Relationship between Vehicle Safety Ratings and Drivers’ Injury Severity in the Context of Gender Disparity

Previous studies have analyzed the relationship between vehicle safety ratings from impact tests and actual crash injury severity. Nevertheless, no study has investigated the relationship in the context of gender disparity. The main objective of this paper is to explore the validity of the 5-star ratings of the U.S. National Highway Traffic Safety Administration, which describes vehicles’ protectiveness, using actual traffic crash data by gender. Random parameter models are developed using 2015–2020 two-vehicle crash data from Maryland, United States. According to the data, over 90% of vehicles have 4–5 stars in overall, front-impact, and side-impact 5-star ratings. After controlling other factors, it is shown that woman drivers are more likely to be seriously injured in two-vehicle crashes than men drivers when using vehicles with the same 5-star safety ratings. Moreover, there is significant individual heterogeneity in the effect of vehicles with different 5-star safety ratings on driver injury severity. Using vehicles with more stars can reduce the risk of being seriously injured for most man drivers. However, the probability of woman drivers being seriously injured is reduced by approximately 5% on average by using vehicles with higher star ratings in the overall and front-impact 5-star rating, and individual heterogeneity shows a difference of nearly 50% in positive and negative effects. The overall and front-impact 5-star ratings of vehicles could not provide reasonable information as the safety performance of vehicles in traffic crashes for woman drivers. On the other hand, drivers’ residence, driving characteristics, crash types, and environmental characteristics are significantly associated with the injury severity. It is expected that the results from this study will contribute to guide a better vehicle safety design for both men and women.
Field study to compare and evaluate winter indoor thermal and health conditions of school buildings with different envelopes

ABSTRACT Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. Previous studies show that Auckland buildings use more energy during winter than other seasons. Auckland building thermal design should focus more on winter indoor thermal conditions. During the winter, high relative humidity can negatively impact indoor health conditions. A conventional Auckland school has a number of low-rise, isolated buildings with lightweight envelopes. In over 90% of Auckland schools, each isolated building only has one to four classrooms. For these types of school buildings, the building envelope becomes the most important design factor for indoor thermal and health conditions. For some energy rating software and design hand books, prescriptions of steady-state R-values ignore the benefits of thermal mass and direct building thermal design towards lightweight wall with high insulation. Based on field study data, this study compares and evaluates indoor thermal and health conditions of classrooms with or without thermal mass in their envelopes.
Grapevine viruses in Mexico: studies and reports

Objective: To contribute to the knowledge of the diversity of viruses and the viral diseases reported in grapevines in Mexico, in order to benefit producers and develop comprehensive viral disease control strategies. Design/methodology/approach: The literature search was conducted in databases such as Scopus, Google Scholar, and EBSCO host, using the following keywords alone or in combination: "virus", "plant", "grapevine", and "Mexico". In addition, the INIFAP database was consulted, alongside undergraduate and postgraduate dissertation theses. Results: Only one academic file was found published in an indexed international journal, using the publication finder software; the report corresponds to a grapevine virus present in Mexico. However, based on all the consulted sources, several viral diseases associated with nine grapevine viruses have been reported in Mexico. These species have been grouped into seven genera and six families. The reports come from Aguascalientes (56%) and Baja California (44%). Three registered viral species are associated with the leafroll complex, three with rugose wood, one with fleck, one with infectious degeneration, and one with red blotch disease. Findings/conclusions: Several grapevine viruses associated with major diseases have been reported in Mexico. Unfortunately, most of the reports lack detail and follow-up, and they are not readily available for international researchers; therefore, the lack of knowledge about this subject in Mexico is significant. Monitoring the epidemiology of viral diseases in the grapevine —a national and international relevant crop— is necessary.