Miracle-dz/UniFAR-FTUs huggingface dataset:
Participation of Electric Vehicle Aggregators in Wholesale Electricity Markets: Recent Works and Future Directions

Electric Vehicles are key to reducing carbon emissions while bringing a revolution to the transportation sector. With the massive increase of EVs in road networks and the growing demand for charging services, the electric power grid faces enormous system reliability and operation stability challenges. Demand and supply disparities create inconsistency in the smooth delivery of electrical power. As a potential solution, EVs and their charging infrastructure can be aggregated to prevent the unwanted effects on power systems and also facilitate ancillary services to the power grid. When not need for transportation purposes, EVs can leverage their batteries for power grid services by participating in the electricity market via mechanisms coordinated by system operators. Hence, the market participation of EV infrastructure can help alleviate the power grid stress during peak periods. However, further research is needed to demonstrate the multiple benefits to both EV owners and power grid operators. This paper briefly overviews the existing literature on market participation of EV aggregators, discuss associated challenges and needs, and propose research directions for future research.
The Materiality of Stone

Contents 1 From Body to Place to Landscape: A Phenomenological Perspective 2 Sprouting Rhizomes and Giant Axes: Experiencing Breton Menhirs 3 From Honey to Ochre: Maltese Temples, Stones, Substances and the Structuring of Experience 4 Frozen Waves and Anomalous Stones: Rock Carvings and Cairns in a Southern Swedish Landscape 5 Conclusions: The Past as Dreamwork
Overview of Data-driven Power Flow Linearization

The accuracy limitation of physics-driven power flow linearization approaches and the widespread deployment of advanced metering infrastructure render data-driven power flow linearization (DPFL) methods a valuable alternative. While DPFL is still an emerging research topic, substantial studies have already been carried out in this area. However, a comprehensive overview and comparison of the available DPFL approaches are missing in the existing literature. This paper intends to close this gap and, therefore, provides a narrative overview of the current DPFL research. Both the challenges (including data-related and power-system-related issues) and methodologies (namely regression-based and tailored approaches) in DPFL studies are surveyed in this paper; numerous future research directions of DPFL analysis are discussed and summarized as well.
Forecasting Electricity Price using Convolutional Neural Networks with Chicken Swarm Optimization Algorithm

Forecasting electricity prices is critical to the efficient operation and planning of power systems, allowing market actors, governments, and consumers to make educated decisions. This abstract provides an overview of a thorough examination and comparison of power price forecasting strategies. This paper proposes a Deep Learning model using Convolutional Neural Networks (CNN) with the Chicken Swarm optimization Algorithm (CSOA) to anticipate changes in the price of power in Australia’s grid. It evaluates them in relation to other cutting-edge models. The CNN architecture is intended to extract hierarchical features from input data by leveraging its capacity to learn spatial and temporal connections. Backpropagation trains the model, adjusting the network’s weights and biases to decrease predicting error. The CSO algorithm improves the optimization process and prevents the CNN from becoming trapped in local optima. CSO uses a population-based search technique to efficiently explore the solution space inspired by the collective behaviors of chickens. We have selected indicators for evaluation that will show how our model outperforms the state-of-the-art approaches at predicting future electricity costs.
Potensi Pemanfaatan Biochar untuk Rehabilitasi Lahan Kering di Indonesia

Abstrak. Pemanfaatan biochar merupakan salah satu upaya pengelolaan limbah pertanian yang prospektif untuk mendorong optimalisasi lahan-lahan suboptimal dan lahan terdegradasi. Tulisan ini bertujuan untuk memberikan informasi tentang potensi biochar di bidang pertanian khususnya dalam upaya merehabilitasi lahan-lahan suboptimal di Indonesia. Di Indonesia, berbagai sumber bahan baku biochar berupa limbah pertanian tersedia cukup banyak yang diperkirakan mencapai 10,7 juta t th-1, di antaranya berupa sekam padi, kulit buah kakao, tempurung kelapa, tempurung kelapa sawit, tongkol jagung. Kualitas biochar yang diproduksi sangat tergantung pada jenis bahan baku, alat pembakaran, suhu pembakaran, dan lamanya pembakaran. Aplikasi biochar pada lahan pertanian berfungsi sebagai pembenah tanah yang mampu memperbaiki sifat kimia tanah (pH, kapasitas tukar kation, N-total, P-tersedia dan Aldd), sifat fisik tanah (Bulk density, porositas dan kemampuan tanah memegang air). Perbaikan kualitas sifat kimia dan fisik tanah tersebut berdampak pada ketersediaan hara dan air melalui kemampuan biochar meretensi hara dan air. Pada akhirnya, penambahan biochar berimplikasi pada peningkatan produktivitas tanaman pangan. Ke depan, diharapkan dengan aplikasi biochar akan semakin luas lahan-lahan suboptimal dan lahan terdegradasi yang dapat dipulihkan dan ditingkatkan produktivitasnya. Abstract. Biochar utilization is prospective land management to encourage optimization of sub-optimal land. The objective of this paper is to inform of potency of biochar in agricultural aspect especially for rehabilitating of degraded land in Indonesia. In Indonesia, the various sources of raw materials such as agricultural wastes available biochar is quite large reaching 10.7 million t / year, such as rice husks, cacao shell, coconut shell, oil palm shell, and corn cob, etc. Quality of biochar produced depends on the type of raw materials, equipment used, combustion temperature, and duration of combustion. Biochar application on agricultural land serves as soil amendment that can improve soil chemical properties (pH, cation exchange capacity, total-N, available P and Alexch), soil physical properties (bulk density, porosity and water holding capacity). Improvement soil physical and chemical properties impacted on the nutrient availability and water availability through nutrient and water retention. Finally the addition of biochar have been impacted for increasing crop productivity. It is expected that addition of biochar will recover widespread of suboptimal land and then land productivity can be increased.
Fault Detection AND Classification in Transmission Lines using Boosted Decision Tree

Fault detection and classification in transmission lines is a crucial task for engineers to maintain reliability and safe operation of electrical power systems. This article proposes a new technique based on statistical features and Boosted Decision Tree (BDT) to identify the fault and classify it. The essential statistical features are calculated from fault currents with 10 different types of faults, then BDT is applied to identify and classify the faults. Experimental results show that the proposed technique can identify and classify transmission line faults accurately. The proposed BDT is compared with other competitive machine learning classifiers to justify the improved performance.
Enhancing sleep postures classification by incorporating acceleration sensor and LSTM model

It has been well established that sleep posture plays a key role in sleep quality monitoring. Consequently, many noncontact and wearable devices, whose systems rely on sensors such as cameras, radar, wireless, and accelerometers, have been developed to classify sleep positions and postures. However, noncontact systems were often unsuccessful when facing limited conditions such as low light and physical obstacles. On the other hand, other systems currently in research, which involves wearable devices, may have used machine learning models but have not competently exploited other more accurate deep learning models. Recognizing scope for improvement, we propose an enhanced five-sleep-posture classification system (5-SPCS) where a novel integration of accelerometer and an LSTM deep learning model can classify sleep postures more efficiently than either one of them does separately. Our experiments showed that the 5-SPCS was capable of outperforming the baselines of existing machine learning-accelerometer systems at 99.6% accuracy.
Generation of hot surface plasmons in graphene by a powerful optical beam

Resonant interaction of two optical beams, with specially adjusted frequencies and wavevectors, mediated by graphene surface plasmons (SPs) and eventually leading to their all-optical generation, was demonstrated experimentally several years ago by measuring the differential reflectance of the probe beam. However, the quantitative explanation of these results requires much larger second-order optical conductivities of graphene than calculations based on standard perturbation theory approaches can yield. We suggest that the observed effect can be understood by considering, in addition to the second-order frequency-difference process, the generation of SPs via interband relaxation of hot electrons created by the powerful pump pulse. We calculate the generation rate of out-of-equilibrium plasmons by the latter mechanism and compare it to other mechanisms of hot carrier relaxation in graphene described in the literature.
Climatic influences on modern coral isotopic records from the Cocos (Keeling) Islands

In comparison to the Pacific Ocean climate, there has been relatively little research into the climate of the Indian Ocean. Recently, however, studies have examined the variability of tropical Indian Ocean climate and the influence of oscillations such as the El Niño Southern Oscillation and the proposed Indian Ocean Dipole. Existing palaeoclimate records from this region, primarily derived from coral geochemistry, are limited and are largely from the western Indian Ocean with few sites in the eastern Indian Ocean tropics. A Porites microatoll from the Cocos (Keeling) Islands, eastern Indian Ocean, was sampled in 1992 and has been analysed to determine the extent of correlation between the corals’ geochemistry and climatic data for the site. In order to look for correlations, Oxygen isotope data and various climatic datasets, including sea surface temperature and precipitation, were analysed statistically, using singular spectral analysis, cross-spectral analysis, multi-taper method analysis, and wavelet analysis in addition to visual analysis, to determine the significance of cycles occurring between 1924 and 1992. As a consequence of initial Oxygen isotope results, StrontiumCalcium analysis was also undertaken for the years 1935 to 1992 and the results were statistically analysed with relation to climate records. SST was shown to be influenced by the El Niño Southern Oscillation and potentially by the Indian Ocean Dipole whereas precipitation did not correlate with either. Neither the SST data nor the precipitation data correlated significantly with the geochemical records at meaningful frequencies. The Oxygen isotopes and Strontium-Calcium ratio of Porites coral at the Cocos (Keeling) Islands did not, therefore, appear to be suitable for use as Palaeoclimate proxies. Further research would be necessary to determine the full range of factors that influence the geochemistry of coral at this isolated site and whether alternative proxies from the coral better correlate with climate conditions at the Cocos (Keeling) Islands. Table of
Rôle de la surface marine sur la variabilité intrasaisonnière estivale de l'atmosphère dans la région Nord Atlantique Europe

Ce travail de these vise a determiner si le couplage de l'atmosphere avec la surface marine joue un role dans la variabilite intrasaisonniere estivale de la circulation atmospherique de grande echelle et si la surface marine peut etre une source de previsibilite potentielle pour l'atmosphere a ces echelles de temps. Un second objectif consiste en l'analyse de l'impact de la representation des processus physiques dans l'ocean superficiel, et en particulier l'impact des variations diurnes oceaniques, sur la representation des temperatures de surface oceanique et sur la circulation atmospherique de grande echelle a des echelles de temps superieures. Pour mener a bien ces travaux, le modele oceanique 1D CNRMOM1D a ete developpe : le choix des parametrisations utilisees dans ce modele vise a optimiser la representation des processus physiques dominant l'evolution des temperatures de surface oceanique aux echelles de temps diurnes a intrasaisonnieres. Les resultats, obtenus a partir de simulations numeriques effectuees avec le modele d'atmosphere ARPEGE-climat force ou couple avec le modele CNRMOM1D, suggerent que les anomalies de temperatures de surface oceanique induites par la circulation atmospherique de grande echelle exercent sur celle-ci une retroaction negative aux echelles de temps intrasaisonnieres : le couplage avec la surface oceanique dans la region Nord-Atlantique Europe (NAE) diminue le nombre de jours de persistance des regimes de temps estivaux de Depression Atlantique, de Blocage et de NAO- d'environ 1 jour ce qui represente 15% de leur persistance moyenne, cette diminution etant variable selon le regime de temps. A partir de simulations forcees du modele CNRMOM1D, on montre que la correction en SST liee a la prise en compte des variations diurnes oceaniques peut atteindre environ 0.3°C a 0.5°C en moyenne journaliere. Cette anomalie peut persister 15 a 40 jours dans les moyennes latitudes, plus de 60 dans les Tropiques. De plus, a partir de simulations couplees avec le modele ARPEGE-climat, on montre que la variabilite diurne oceanique peut affecter l'etat moyen estival par une diminution du gradient meridien de SST, une diminution de l'extension de la glace de mer, une anomalie de circulation atmospherique de grande echelle qui se projette sur une phase positive de la NAO ainsi que des modifications de la couverture nuageuse et des profils d'humidite atmospherique. Ce travail montre les ameliorations potentielles, en termes d'etats moyens oceanique et atmospherique et en termes de variabilite intrasaisonniere, que peuvent apporter un couplage a frequence horaire et l'utilisation d'un modele de circulation generale oceanique a haute resolution verticale dans les simulations couplees ocean-atmosphere.
AIDS Care : Psychological and Socio-medical Aspects of AIDS / HIV

Altruism motivates participation in a therapeutic HIV vaccine trial (CTN 173) Louise Balfour a b , Kimberly Corace a b , Giorgio A. Tasca a b , Cécile Tremblay c , JeanPierre Routy d & Jonathan B. Angel a b a The Ottawa Hospital , University of Ottawa , Ottawa, ON, Canada b Ottawa Hospital Research Institute (OHRI) , Ottawa, ON, Canada c Centre Hospitalier de l'Université de Montréal (CHUM) , Montreal, QC, Canada d McGill University Health Centre and McGill University , Montreal, QC, Canada Published online: 09 Oct 2010.
Noise Induces Hopping between NF-kappa B Entrainment Modes

SUMMARY Intracellular oscillators entrain to periodic signals by adjusting their phase and frequency. However, the low copy numbers of key molecular players make the dynamics of these oscillators intrinsically noisy, disrupting their oscillatory activity and entrainment response. Here, we use a combination of computational methods and experimental observations to reveal a functional distinction between the entrainment of individual oscillators (e.g., inside cells) and the entrainment of populations of oscillators (e.g., across tissues). We demonstrate that, in the presence of intracellular noise, weak periodic cues robustly entrain the population averaged response, even while individual oscillators remain un-entrained. We mathematically elucidate this phenomenon, which we call stochastic population entrainment, and show that it naturally arises due to interactions between intrinsic noise and nonlinear oscillatory dynamics. Our ﬁndings suggest that robust tissue-level oscillations can be achieved by a simple mechanism that utilizes intrinsic biochemical noise, even in the absence of biochemical couplings between cells. and 59% for the constant initial-states and the random initial-states situations respectively, again indicating that the overall enhancement effects are quite similar. However it is noteworthy that this effect is slightly more when the initial states are randomized. These numerical experiments with the NF- k B model clearly show that static noise, in the form of randomized initial states, is not responsible for the phenomenon we report and dynamical noise is necessary to see the proposed effect. In the case of weak forcing, this insight can also be obtained from the mathematical analysis we present later for a simple example.
Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE

Objectives To review studies developing or validating a prognostic model for individual venous thromboembolism (VTE) recurrence risk following cessation of therapy for a first unprovoked VTE. Prediction of recurrence risk is crucial to informing patient prognosis and treatment decisions. The review aims to determine whether reliable prognostic models exist and, if not, what further research is needed within the field. Design Bibliographic databases (including MEDLINE, EMBASE and the Cochrane Library) were searched using index terms relating to the clinical field and prognosis. Screening of titles, abstracts and subsequently full texts was conducted by 2 reviewers independently using predefined criteria. Quality assessment and critical appraisal of included full texts was based on an early version of the PROBAST (Prediction study Risk Of Bias Assessment Tool) for risk of bias and applicability in prognostic model studies. Setting Studies in any setting were included. Primary and secondary outcome measures The primary outcome for the review was the predictive accuracy of identified prognostic models in relation to VTE recurrence risk. Results 3 unique prognostic models were identified including the HERDOO2 score, Vienna prediction model and DASH score. Quality assessment highlighted the Vienna, and DASH models were developed with generally strong methodology, but the HERDOO2 model had many methodological concerns. Further, all models were considered at least at moderate risk of bias, primarily due to the need for further external validation before use in practice. Conclusions Although the Vienna model shows the most promise (based on strong development methodology, applicability and having some external validation), none of the models can be considered ready for use until further, external and robust validation is performed in new data. Any new models should consider the inclusion of predictors found to be consistently important in existing models (sex, site of index event, D-dimer), and take heed of several methodological issues identified through this review. PROSPERO registration number CRD42013003494.
Comorbidity and confounding factors in attention-deficit/hyperactivity disorder and sleep disorders in children

: Sleep problems are commonly reported in children with attention-deficit/ hyperactivity disorder (ADHD) symptoms. Research data regarding the complex and reciprocal relationship between ADHD and sleep disturbances has now accumulated. This paper is focused on the types of sleep problems that are associated with ADHD symptomatology, and attempts to untangle confounding factors and overlapping symptoms. The goal is also to present an updated overview of the pathophysiology of and treatment strategies for sleep problems in children with ADHD. The review also points out that future research will be needed to clarify further the other psychiatric comorbidities and side effects of medication in order to improve treatment outcomes and prevent misdiagnosis in clinical practice.
The Equity Premium

Recent research on the equity risk premium has questioned the ability of historical estimates of the risk premium to provide reliable estimates of the expected risk premium. We calculate the equity risk premium for a number of countries over longer horizons than has been attempted to date. We show that the realised US equity premium is consistent with the premia obtained elsewhere. Furthermore, using well over a century of data, we find that current estimates of the equity premia are close to those observed during the pre-1914 era. This is of particular relevance given the argument that the financial environment during that period bears a closer resemblance to today than the 1914-1945 period, and possibly also the 1945-1971 period. This points to a current equity risk premium that is considerably lower than consensus forecasts (Welch 2001).
Apr 27, 2019 Methods and Processes of Developing the Strengthening the Reporting of Observational Studies in Epidemiology -

Modiﬁcations or additions were made to the STROBE items numbered as follows: 1 (title and abstract), 3 (objectives), 5 (setting), 6 (participants), 7 (vari-ables), 8 (data sources/measurement), 9 (bias), 10 (study size), 12 (statistical methods), 13 (participants), 14 (descriptive data), 15 (outcome data), 16 (main results), 17 (other analyses), 19 (limitations) and 22 (funding). Published literature was not always available to support modiﬁcation to, or inclusion of, an item. The methods and processes used in the development of this statement were similar to those used for other extensions of the STROBE statement. The use of this extension to the STROBE statement should improve the reporting of observational studies in veterinary research related to animal health, production, welfare or food safety outcomes by recognizing the unique features of observational studies involving food-producing and companion animals, products of animal origin, aquaculture and wildlife.
Telework and technostress in educational organizations: Lessons from the COVID-19 pandemic in Mexico

This research aims to explain, in the context of the COVID-19 pandemic, the effect that the characteristics of telework that teachers have on techno-stress in Mexican educational organizations belonging to the public sector from preschool to undergraduate. The methodology was empirical-statistical, the data were obtained from the application of 835 surveys to teachers and were analyzed by means of the structural equation technique using second order variables. The results indicate that resources, autonomy and worklife balance are characteristics of the telework performed by teachers that explain the increase of technostress in terms of fatigue, anxiety and inefficacy when distance classes are developed, in addition, differentiated findings are presented based on the sex of the teachers. The results imply information for learning and organizational decision making by educational authorities