Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Pollutants of Emerging Concern in Aquatic Media Through E-PRTR Regulation.A Case Study: Cordoba, Spain, 2009-2018

The E-PRTR EU Regulation can be followed for the evaluation of the level of pollutants of emerging concern in treated wastewater. This regulation is of regional responsibility in the UE, and establishes for the Andalusian region of Spain the following pollution parameters as mandatory to be controlled periodically in treated wastewater in Waste Water Treatment Plants (WWTPs) with more than 100.000 equivalent inhabitants of treatment capacity: COD, N-Kjeldahl, total P, Cl-, F- (conventional pollution); As, Cd, Cr, Cu, Hg, Ni, Zn and Pb, as heavy metals; PAHs (polycyclic aromatic hydrocarbons), adsorbed organic halides (AOXs), benzene and chloroform, as organic compounds. This paper shows results obtained in the application of the E-PRTR Regulation to the wastewater of Cordoba during 2009-2018. As shown, average of COD, N-Kjeldahl an total P values, respectively, in urban and treated wastewater were 604 and 89 mg/L, 54.1 and 33.4 mg/L and 3.4 and 1.4 mg/L. With respect to heavy metals, the mean content in treated wastewater was 0.135 mg/L, starting from 0.226 mg/L in raw wastewater. The majority of these are Cu and Zn (0.043 mg/L and 0.107 mg/L, respectively, in raw wastewater). For pollutants of emerging concern, the mean content of PAHs was 13 ng/L in treated water vs 31 ng/L in raw wastewater. Moreover, concentration of AOXs in raw wastewater was of 20 ng/L while in treated wastewater decreased up to 16 ng/L. Also, benzene content in raw wastewater and treated wastewater decreased from 40 ng/L to 11 ng/L. Finally, the major organic compound was chloroform, with a level in raw wastewater of 5.6 ng/L that was reduced along the treatment up to 3.2 ng/L. The provided data indicated a low concentration of the compounds of emerging concern in the wastewater of Cordoba and its minimal impact on the receiving aquatic environment (the Guadalquivir river).
Supplementary Material for Teacher Guided Architecture Search

We follow the method proposed by [14] to learn the probability of hyperparameter choices (X = x1, x2, ., xn) that maximize the unknown but observable reward function f : X → R. A 2-layer long short-term memory (LSTM) is used as the controller that chooses each hyperparameter in the network at every unrolling step. The LSTM network, models the conditional probability distribution of optimal hyperparameter choices as a function of all previous choices P (xj |x1, x2, ., xj−1, θ) in which θ is the set of all tunable parameters in the LSTM network. Since a differentiable loss function is not known for this problem, usual maximum likelihood methods could not be used in this setting. Instead parameters are optimized through reinforcement learning based approaches (e.g. REINFORCE [12]) by increasing the likelihood of each hyperparameter choice according to the reward (score) computed for each sampled network (or a batch of sampled networks). Relative to [14], we made two modifications. First, since the order of dependencies between different hyperparameters in each layer/block is arbitrary, we ran the LSTM controller for one step per layer (instead of once per hyper-parameter). This results in shorter choice sequences generated by the LSTM controller and therefore shorter sequence dependencies. Second, we chose a Boltzman policy method for action selection to allow the search to continue the exploration throughout the search experiment. Hyperparameter values were selected according to the probability distribution over all action choices. Compared to -greedy method, following the softmax policy reduces the likelihood of sub-optimal actions throughout the training. For each hyperparameter, choice probability is computed using a linear transformation (e.g. WKh ,WNfilters ) from LSTM output at the last layer (hl ) followed by a softmax. To reduce the number of tunable parameters and more generalization across layers, we used shared parameters between layers.
Chapter 2 Deterministic Unit Commitment Models and Algorithms

This chapter introduces the basic formulations of unit commitment problems which are generally proposed to optimize the system operations by mixed integer linear programming. Meanwhile, the formulations target a series of external factors that affect electrical power generation schedules, such as ramping capacity, reserve requirement, transmission capacity, fuel constraint and emission. This chapter also introduces the solution approaches to solve the deterministic unit commitment problems, especially using Lagrangian Relaxation and Benders’ Decomposition. The SCUC cases are provided to illustrate the UC modeling and decomposition processes. All formulation notations are listed in Appendix B for reference.
Postoperative morbidity following Whipple’s procedure for periampullary carcinoma: a retrospective study spanning 5 years

Background: The morbidity rates for Whipple’s procedure has remained high even as mortality rates were coming down. This study was intended to assess postoperative morbidity rates in a tertiary care centre and to compare it with other centres.Methods: Data was collected from various registers and medical records for this retrospective cohort study. All Whipple’s procedures for 5 years were included in the study. Statistical analysis was done using R statistical software and the results were tabulated.Results: There were 48 patients and half of them developed morbidity. Surgical site infection was the most common complication (18.8%) followed by pulmonary complications (12.5%) and bile leak (6.25%). Half of the patients having pulmonary complications died while nobody with surgical site infection or bile leak died.Conclusions: In this study the morbidity rates were comparable to other centres. Hypoalbuminemia is a significant predictor of morbidity. Surgical site infection was the most common morbidity. Pulmonary complications were the most common cause for death. Morbidity rate is comparable to other centres and Whipple’s procedure is a safe surgery in the tertiary centre where the study was conducted.
Islamic Tourism: A Form of Harmonization of Religion, Politics, Social, Culture and Economy

Most research concluded that the development of Islamic tourism was associated with business and economic factors, namely the matter of seeking benefits from the development of Muslim tourism behavior. Research on Islamic tourism only made the connection between religion and tourism behavior but it did not examine the increasing awareness of Muslims in their obedience to sharia. This article aimed to compare the results of research on the development of Islamic tourism in various countries, both those with a majority of Muslim population and those which are not. This study applied a qualitative approach and chose a literature study to examine the data. In addition, research studies on the development of Islamic tourism provided other variations of the causes of the tourist variants development, namely political factors. The development of Islamic tourism in North Africa, Middle East and Asia, in general, is an impact of Islam after the WTC tragedy and in Thailand, Islamic tourism is part of conflict resolution in
ANALYSIS OF OPEN-PIT MINING ACTIVITIES USING SENTINEL-1A/B COHERENCE IMAGERY

ABSTRACT: Open-pit mining is one of the surface mining technique extracting minerals from the surface. As openpit mines are often rock fields with sparse vegetation, Interferometric Synthetic Aperture Radar (InSAR) technique can be used effectively. InSAR coherence detects random surface change that measures the activity or stability of the surface using interferometric phase data. High coherence will be maintained on the surface where there is no movement and only surface scattering. On the other hand, the surface where there is a lot of movement and volumetric scattering has low coherence value. Therefore, using 12-day InSAR coherence images from Sentinel-1A/B satellites, for example, it is possible to analyze how active the open-pit mine is during the 12 days. The Musan mine in North Korea is the largest open-pit iron mine in Asia with the proved reserves of about 2.06 billion tons and more than 9 square kilometers. We used a total of 102 SAR images of Sentinel-1A/B distributed freely from European Space Agency (ESA) from June 2015 to April 2019 and over 100 scenes of 12-day InSAR coherence data were obtained. Stable and moving spots were selected through the average and standard deviation of the entire coherence time series data. Coherence values include not only the mining activity but also the effects of perpendicular baseline, temporal baseline, and weather condition. Therefore, Normalized Difference Activity Index (NDAI) is newly defined to remove the noise and only the coherence variation due to the influence of the mining activity was extracted. Observation shows various mining activities in time. This is a preliminary study that can be verified through comparison with other relevant data such as seismic or acoustic data.
Design of a Mini Combined Heat and Power Cycle for Naval Applications

The themes of energy conversion with low environmental impact and energy recovery, will have, in the near future, a high potential for development for naval applications. The containment of pollutant emissions can be achieved by an innovative mini gas-steam combined cycle with thermal energy cogeneration to feed the ship thermal utilities, in place of or alongside the electric diesel engines currently used. The present work is focused on the definition of the architecture of the system, by selecting optimal thermodynamic cycle parameters and power repartition, as well as on the choice and sizing of the individual components to obtain a compact and high efficiency system. The proposed basic mini-cycle consists of a gas turbine of about 1.5 MW and a steam turbine of about 0.5 MW. For an overall electrical efficiency of about 28%, a total return (thermal + electricity) of 75% can been achieved. An example of plant providing larger power, in a partially modular arrangement is also proposed. * Corresponding author Barsi, D. , et al. Design of a Mini Combined Heat and Power . Year 2020 Volume 8, Issue 2, pp 281-292 Journal of Sustainable Development of Energy, Water and Environment Systems 282
k-anonymization May Be NP-Hard, but Can it Be Practical?

While it is well-known that producing a k-anonymous microdata set is computationally difficult [2], there is very little information on application of k-anonymity to real-world microdata. This paper attempts to examine the practicality of producing a k-anonymous microdata set and assess whether or not the resulting microdata can be used to produce estimates reasonably close to estimates produced using the original microdata. This paper does not take the position that k-anonymity, by itself, is sufficient to limit risk of disclosure from all possible intrusion scenarios; rather, this paper seeks to explore whether or not k-anonymity microdata sets may be produced in a reasonable amount of time and whether k-anonymity may be used as part of a larger statistical disclosure treatment process.
AMEP_A_219104 805..812

Sajita Setia 1 Jam Chin Tay 2 Yook Chin Chia 3 Kannan Subramaniam 4 1Transform Medical Communications, Wanganui, New Zealand; 2Department of General Medicine, Tan Tock Seng Hospital, Singapore, Singapore; 3Department of Medical Sciences, School of Healthcare and Medical Sciences, Sunway University, Bandar Sunway, Selangor Darul Ehsan, Malaysia; 4Research, Development and Medical, Emerging Markets, Upjohn – a Pfizer Division, Sydney, New South Wales, Australia Abstract: Continuing medical education (CME) is meant to not only improve clinicians’ knowledge and skills but also lead to better patient care processes and outcomes. The delivery of CME should be able to encourage the health providers to accept new evidencebased practices, and discard or discontinue less effective care. However, continuing use of expensive yet least effective and inappropriate tools and techniques predominates for CME delivery. Hence, the evidence shows a disconnect between evidence-based recommendations and real-world practice – borne out by less than optimal patient outcomes or treatment targets not being met especially in lowto middle-income countries. There is an ethical and professional obligation on CME-providers and decision-makers to safeguard that CME interventions are appraised not only for their quality and effectiveness but also for costeffectiveness. The process of learning needs to be engaging, convenient, user-friendly and of minimal cost, especially where it is most needed. Today’s technology permits these characteristics to be integrated, along with further enhancement of the engagement process. We review the literature on the mechanics of CME learning that utilizes today’s technology tools and propose a framework for more engaging, efficient and cost-effective approach that implements massive open online courses for CME, adapted for the twenty-first century.
Predictive performance model for hydraulic occulator design with polyaluminum chloride and aluminum sulfate coagulants

Mechanistically-based scalable algorithms for design and operation of hydraulic occulators were developed in this research based on observations of residual turbidity for a range of in uent turbidities (5−500NTU) and coagulant doses (0.01−0.15mM Al), for two hydraulic residence times (800 s and 1200 s) and for two coagulant types (polyaluminum chloride and aluminum sulfate). Data were obtained over a range of sedimentation capture velocities using a bench-scale laminar ow tube occulator and quiescent settling column. Seemingly disparate results were uni ed through creation of a composite design parameter that considers collision potential in the occulator and coagulant surface coverage of colloids. One adjustable model parameter was used to t data (R2 ≈ 0.9) from over 136 experiments to create a model for each of the two coagulants. The model is applicable over a range of sedimentation tank capture velocities and accurately re ects the e ects of coagulant dose, raw water turbidity, occulator residence time, and coagulant type. The model was validated by successfully predicting results from independent data sets. When calibrated properly to the coagulant and source water to be treated, the predictive model is expected to be a useful tool in the design and operation of hydraulic occulators.
University of Groningen Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead Sabatelli,

In this paper we propose a novel supervised learning approach for training Artificial Neural Networks (ANNs) to evaluate chess positions. The method that we present aims to train different ANN architectures to understand chess positions similarly to how highly rated human players do. We investigate the capabilities that ANNs have when it comes to pattern recognition, an ability that distinguishes chess grandmasters from more amateur players. We collect around 3,000,000 different chess positions played by highly skilled chess players and label them with the evaluation function of Stockfish, one of the strongest existing chess engines. We create 4 different datasets from scratch that are used for different classification and regression experiments. The results show how relatively simple Multilayer Perceptrons (MLPs) outperform Convolutional Neural Networks (CNNs) in all the experiments that we have performed. We also investigate two different board representations, the first one representing if a piece is present on the board or not, and the second one in which we assign a numerical value to the piece according to its strength. Our results show how the latter input representation influences the performances of the ANNs negatively in almost all experiments.
Cuantificación del flujo coronario por imágenes en pacientes con cardiopatía isquémica

Resumen La cuantificacion del flujo sanguineo miocardico se ha convertido en uno de los principales retos de la cardiologia actual. Dentro de las tecnicas nucleares, la tomografia por emision de foton unico (SPECT) con Tl-201 o Tc-99m-Sestamibi, es una de las mas empleadas, principalmente por su disponibilidad. Este metodo involucra un analisis semicuantitativo del flujo sanguineo miocardico regional. La tomografia por emision de positrones (PET) con 13 N-amonia es considerada como el metodo no invasivo de mayor precision para la cuantificacion del flujo miocardico y la reserva de flujo coronario. La medicion objetiva de estos valores de flujo nos permite detectar la presencia de enfermedad coronaria incipiente, lo cual es de gran valor para pacientes con coronarias sin lesiones por angiografia, pero con factores de riesgo cardiovascular (diabetes, hipertension, dislipidemia, tabaquismo). La medicion cuantitativa del flujo sanguineo miocardico mediante PET con 13 N-amonia nos permite establecer la repercusion de lesiones coronarias, aunque estas no se asocien a estenosis angiograficamente significativas. Summary
Improved 1-km-resolution PM2.5 estimates across China
using the space-time extremely randomized trees

Abstract. Fine particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) shows adverse effects on human health and atmospheric environment. Satellite-derived aerosol products have been intensively adopted in estimating surface PM2.5 concentrations, but most previous studies failed to monitor air pollution over small-scale areas limited by coarse spatial-resolution (3–50 km) and low data-quality aerosol optical depth (AOD) products. Therefore, a new space-time extremely randomized trees (STET) model is developed that integrates spatiotemporal information to improve PM2.5 estimates at both spatial resolution and overall accuracy across China. To this end, the newly released MODIS MAIAC AOD product, meteorological and other auxiliary data are inputs to the STET model. Daily 1-km PM2.5 maps in 2018 across mainland China are produced. The STET model performs well with a high out-of-sample (out-of-station) cross-validation coefficient of 0.89 (0.88), a low root-mean-square error of 10.35 (10.97) μg/m3, a small mean absolute error of 6.71 (7.17) μg/m3, and a small mean relative error of 21.37 % (23.77 %), respectively. Particularly, it can well capture the PM2.5 concentrations at both regional and individual site scales. In addition, it posed a strong predictive power (e.g., monthly-R2 = 0.80) and can be used to predict the historical PM2.5 records. The North China Plain, the Sichuan Basin, and Xinjiang Province always are featured with high PM2.5 pollution, especially in winter. The STET model outperforms most models presented in previous related studies. More importantly, our study provides a new approach to obtain high-quality PM2.5 estimates, which is important for air pollution studies over urban areas.
Align, Attend and Locate: Chest X-Ray Diagnosis via Contrast Induced Attention Network With Limited Supervision

Obstacles facing accurate identification and localization of diseases in chest X-ray images lie in the lack of high-quality images and annotations. In this paper, we propose a Contrast Induced Attention Network (CIA-Net), which exploits the highly structured property of chest X-ray images and localizes diseases via contrastive learning on the aligned positive and negative samples. To force the attention module to focus only on sites of abnormalities, we also introduce a learnable alignment module to adjust all the input images, which eliminates variations of scales, angles, and displacements of X-ray images generated under bad scan conditions. We show that the use of contrastive attention and alignment module allows the model to learn rich identification and localization information using only a small amount of location annotations, resulting in state-of-the-art performance in NIH chest X-ray dataset.
DESIGN AND IMPLEMENTATION OF HYBRID CASCADED ENERGY EFFICIENT KOGGE STONE ADDER

Addition plays a vital role in all arithmetic operations. It is used widely in many VLSI systems such as application specific DSP architecture and microprocessor architecture. The energy efficient designs have gained more recent attention and for highly employed functional units, especially for the adders. The energy consumption of an adder depends on the circuit minimizing, the addition procedure, the recurrence structure and the wiring complexity. Weinberger and Ling are the two most commonly used binary addition algorithms that are used in adders. This paper gives the performance evaluation of addition algorithms on Kogge-Stone arrangement and have been observed to save energy by the proper selection of addition algorithms in 16-bit adders. The design of Kogge-stone adder has been carried out by using TANNER EDA tool. The efficiency ofthe adder design can be improved by prefix selection, the algorithm, computational sum and logic depth. When compared to Weinberger algorithm, the number of gates used is less in case of the proposed ling recurrence algorithm.
Household characteristics and food insecurity and their association with nutritional outcome of under-five children of a rural farming community of Sokoto State, Nigeria.

Background: Malnutrition is a global problem and continues to be one of the major health problems among children particularly for the poor and underprivileged as poverty remain a fundamental cause of household food insecurity and consequently malnutrition. Objective: To determine household characteristics, food Security status and their association with nutritional status of under five children of a rural community. Methodology: A community-based descriptive cross-sectional study was conducted among 200 households’ in a rural community. Sampled households with eligible children were selected using multistage sampling technique. Interviewer-administered questionnaires were used to collect data through face-to-face interview. Data was analyzed using SPSS version 23.0. Both univariate and bivariate analyses were carried out. Statistically significant level was set at p<0.05. Results: Respondents average age was 42; IQR: 33-51 years. Nearly two-thirds (62.8%) had only Qur’anic education. More than three quarters (86.8%) of respondents experienced food shortage in the recent past, 47.9% are food insecure and 24.5% of the under-five children were acutely malnourished. Respondents ’ age (p=0.001); households head educational level (p=0.001); family composition (p=0.001); type of household food insecurity suffered (p=0.001) showed statistically significant association with children nutritional status. Conclusion: A significant proportion of the households head are of low-social status and food insecure. Majority of households in the recent past experienced food shortage and a quarter of under-five children were acutely malnourished.
Self-Microemulsifying System

Oral route is preferred for drug administration; however according to the recent scenario 40% of new drug candidates have poor water solubility and low bioavailability. One of the biggest challenges in drug delivery science is to improve low oral bioavailability problem which is associated with the hydrophobic drugs due to their unprecedented potential as a drug deliver with the broad range of application. Self-emulsifying systems have been proved as highly useful technolog-ical innovations to vanquish such bioavailability problem by virtue of their dimin-utive globule size, higher solubilization tendency for hydrophobic drugs, robust formulation advantages, and easy to scale up. Self-microemulsifying systems are isotropic mixers of oil, surfactant, drug and co-emulsifier or solubilizer, which spontaneously form transparent micro-emulsions with oil droplets ranging between 100 and 250 nm. Micro emulsified drug can be easily absorbed through the lymphatic pathway and it bypasses the hepatic first-pass effect. Self-microemulsifying system is a thermodynamically stable system and overcomes the drawback of layering of emulsions after sitting for a long period of time. The present literature gives exhaustive information on the formulation design and characterization of self-microemulsifying systems.