Miracle-dz/UniFAR-FTUs huggingface dataset:
Reward-Free Policy Space Compression for Reinforcement Learning

In reinforcement learning, we encode the potential behaviors of an agent interacting with an environment into an infinite set of policies, the policy space, typically represented by a family of parametric functions. Dealing with such a policy space is a hefty challenge, which often causes sample and computation inefficiencies. However, we argue that a limited number of policies are actually relevant when we also account for the structure of the environment and of the policy parameterization, as many of them would induce very similar interactions, i.e., state-action distributions. In this paper, we seek for a reward-free compression of the policy space into a finite set of representative policies, such that, given any policy $\pi$, the minimum R\'enyi divergence between the state-action distributions of the representative policies and the state-action distribution of $\pi$ is bounded. We show that this compression of the policy space can be formulated as a set cover problem, and it is inherently NP-hard. Nonetheless, we propose a game-theoretic reformulation for which a locally optimal solution can be efficiently found by iteratively stretching the compressed space to cover an adversarial policy. Finally, we provide an empirical evaluation to illustrate the compression procedure in simple domains, and its ripple effects in reinforcement learning.
Simulation and tests on surge arresters in high-voltage laboratory

High-voltage impulse generator is standard equipment in high-voltage laboratories where it is normally used for dielectric tests on power apparatus and equipment. Flexibility to carry out several kind of test for industrial services and applied research is suitable for general-purpose laboratories. In this way, computational simulation of devices and equipment is a useful tool for optimizing test capabilities of such laboratories. This contribution relates our experience in application of an h-v impulse generator as an impulse current generator for standard tests on metal-oxide surge arresters in the lower range of distribution voltage. The impulse current attainable with the generator and the measuring procedure were simulated modeling the generator circuit and the non-linear load of arresters by the Alternative Transient Program (ATP) and a simplified version of the frequency-dependent model recommended by the IEEE WG 3.4. 11. Tests were performed on metal-oxide surge arresters without information on the residual voltages provided by the manufacturer. Satisfactory agreement is obtained between measurement and simulation, confirming the circuit model and parameters adjustment procedure proposed by the authors and, moreover, it confirms that simulation is useful to improve the laboratory test capacity.
Influence of solar cycle and chemistry on tropical (10°N–15°N) mesopause variabilities

Monthly averaged zonal mean temperature and ozone volume mixing ratios obtained from “Sounding of the Atmosphere using Broadband Emission Radiometry” instrument on board “Thermosphere Ionosphere Mesosphere Energetics and Dynamics” satellite for the years 2002–2012 are used to study the seasonal and solar cycle variabilities of tropical (10°N–15°N) mesopause structure. The mesopause temperature and ozone mixing ratios are positively correlated with solar cycle due to changes in CO2 and O, respectively. Although the seasonal variation in mesopause temperatures is quite small, the mesopause altitudes are comparatively higher (~99–100 km) in April and lower (~95 km) in September. The factors controlling the tropical mesopause structure are investigated by taking the mesopause variability for the year 2011 as a case study as it resembles the long‐term mean seasonal variation. It is found that the radiative cooling due to 15 µm CO2 infrared emissions is the only cooling mechanism in the mesopause region. The net heating rates obtained from (i) solar heating by O2 and O3, (ii) chemical heating due to seven major exothermic reactions, (iii) O3 long‐wave radiative heating, and (iv) CO2 cooling are smaller (~20 K/d) in April and larger (~85 K/d) in September at lower thermosphere (~99–101 km). The downward heat conduction from the lower thermosphere forces the mesopause to lower heights in September, although no downward heat conduction is observed in April.
Structural, Spectroscopic and Optical Properties of Monohydrated Adenine: A Theoretical Study

The structural, spectroscopic (IR, NMR and UV-Vis), electronic and optical properties of monohydrated adenine (monohydrated 6-aminopurine, C5H5N5.H2O) are investigated theoretically using DFT/B3LYP level of theory. Three minimum energy structures have been identified for monohydrated of adenine where H2O molecule is doubly hydrogen bonded with adenine.1H NMR analysis shows that the protons which are hydrogen bonded become deshielded and chemical shift moves to the higher frequency region.Five IR active mode of vibrations were found at 3108, 3295, 3665, 3676 and 3719 cm-1 which are assigned as bonded -OH vibration of H2O, Bonded -NH vibration of NH2, Free -NH vibration of adenine (9 N), Free -NH vibration of NH2, Free -OH vibration of H2O, respectively and agree well with the available experimental results. The investigation of electronic properties shows that the HOMO-LUMO band gap energy of monohydrated adenine at B3LYP level is 5.15 eV. The major electronic transition (from HOMO to LUMO (83%) (π→π*)) occurs at 258 nm (4.80 eV) with a minor transition at 237 nm (5.23 eV). Theoretically it is observed that the HOMO-LUMO band gap energy is for monohydrated adenine is lower than that of adenine.
Insights into the extraction mechanism from the coordination chemistry of copper(II) with a synergistic mixture which mimics Versatic10 and 2-ethylhexyl 4-pyridinecarboxylate ester

Abstract In the present work, a copper(II) synergist complex with methyl isonicotinate (LI, a short chain analog of 2-ethylhexyl 4-pyridinecarboxylate ester) and isobutyric acid (HBI, a short chain analog of Versatic10) was synthesized and studied by X-ray single-crystal diffraction. The results indicated that the copper(II) synergist complex obtained with isobutyric acid and methyl isonicotinate crystallizes in the monoclinic C2/c space group and confirmed the composition [Cu(BI)2(LI)]2. The crystal structure consisted of centrosymmetric dimeric units, in which the two Cu ions are bridged in pairs by four carboxylate groups of the deprotonated isobutyric acid. In order to bridge the gap between the solid-state structure of the copper(II) synergist complex obtained with isobutyric acid and methyl isonicotinate and the solution structure of the extracted copper(II) complex in the non-polar organic phase, the two copper(II) complexes were further investigated by Fourier transform infrared spectroscopy (FT-IR) and electrospray ionization mass spectrometry (ESI-MS). The results indicated that the extracted copper(II) complex in the non-polar organic phase has a similar coordination structure as the copper(II) synergist complex obtained with isobutyric acid and methyl isonicotinate.
Review—Surface-Enhanced Raman Scattering Sensors for Food Safety and Environmental Monitoring

This article gives a review of surface-enhanced Raman scattering (SERS) sensors for food safety and environmental pollution monitoring. It introduces the basic concepts of SERS substrates, SERS enhancement factors and mechanisms, SERS probes/labels, molecular recognition elements as well as optoﬂuidic SERS devices (SERS sensors integrated with microﬂuidics). This article places an emphasis on the design strategies of various SERS sensors by utilizing ﬁngerprinting SERS spectra or by using SERS probes. It highlights the applications of SERS sensors in detection of heavy metals (such as Hg 2 + , Pb 2 + , Cd 2 + and As 3 + ), inorganic anions (nitrite, nitrate, perchlorate and ﬂuoride), toxic small molecules (polycyclic aromatic hydrocarbon, polychlorinated biphenyls, herbicides, pesticides, antibiotics and food additives), as well as pathogens (bacteria and viruses). the strategy based on the on a ﬁlm, 2 simultaneously at LOD of pM, 1 50 nM, respectively. These studies along with other that of
Investigation of antioxidant activity of active compounds in ethyl acetate crude extract from stem of Paederia foetida Linn.

This research presents the antioxidant activity of active compounds in ethyl acetate crude extract from the stem of Paederia foetida Linn.by using a 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging method. Antioxidant activity of ethyl acetate crude was investigated and the percentage of inhibition was 74.72%, indicating a good antioxidant activity. The ethyl acetate crude was then isolated by a silica gel column chromatography method. It was found that one separated fraction showed high percentage (59.15%) in the inhibition. The functional group and structure of the compound in this fraction was then analyzed via Fourier Transform Infrared Spectroscopy (FT-IR), Nuclear Magnetic Resonance (NMR) spectroscopy and Thin Layer Chromatography (TLC). These evidences implied that the fraction containing active compounds possibly composed of the flavonoid derivatives having hydroxyl and methyl groups as the substituent groups.Keywords: 2,2-diphenyl-1-picrylhydrazyl free scavenging, antioxidant, Paederia foetidaLinn.
QUALITY ATTRIBUTES OF PANCAKES FROM PEELED AND UNPEELED SWEETPOTATO FLOURS WITH CASSAVA STARCH

The prevalence of celiac disease (CD), an intolerance of gluten, has been reported to be as high as one in 200 of the world population (Fasano and Catassi, 2001). ABSTRACT This study evaluated some quality attributes of pancakes from peeled and unpeeled sweetpotato flours and cassava starch. Cassava starch was substituted up to 30% of the total composite flour. The proximate composition, colour, carotenoid and functional properties of the different flour blends were determined. The flour blends were processed into pancakes and the proximate composition and sensory acceptability of the pancakes were determined. Data obtained were subjected to analysis of variance. The result showed that they were significant differences (p<0.05) in the functional properties of the flour blends. Bulk density, Water absorption capacity, Oil absorption capacity, swelling capacity ranged from 0.70 to 0.78 g/ml, 1.87 to 2.30 g/ml, 1.02 to 1.40 g/ml and 5.18% to 6.66% respectively. There were significant differences (p<0.05) in the proximate composition of the pancake samples. The values ranged from 42.76 to 45.53%, 2.13 to 3.98%, 9.06 to 10.34%, 5.01 to 7.18%, 3.75 to 6.01% and 29.19 to 35.33% for moisture, ash, fat, protein, crude fibre and carbohydrate contents, respectively. Pancake produced from 100:0 peeled and unpeeled sweetpotato flour had the highest score for overall acceptability which can compare favorably, with pancakes from wheat flour which is the control sample. In conclusion, sweetpotato flour blended with cassava starch at different ratio gave good proximate and functional properties which resulted in pancakes of good quality attributes.
Training DNNs II

where δ is a small positive value to avoid encountering the undefined gradient of √ z at z = 0 At test time, μ and σ may be replaced by running averages that were collected during training time. So the model can be evaluated on a simgle example. Normalizing the mean and standard deviation of a unit can reduce the expressive power of the neural network containing that unit. In order to maintain the expressive power of the network, it is common to replace the batch of hidden unit activationsH with γH + β rather than simply the normalized H . In sum, learnable parameters are μ,σ,γ,β, and in practice, it is recommended to normalizeXH rather thanX .
SUBCAPSULAR LIVER HEMATOMA – A COMPLICATION AFTER LAPAROSCOPIC CHOLECISTECTOMY

Subcapsular liver haematoma is among the most severe complications after laparoscopic cholecystectomy, but occurs rarely. The hematoma is usually located around the right lobe of the liver (in 75% of patients). We report the case of a 71 year old patient who underwent laparoscopic cholecystectomy for acute cholecistitis. Initial postoperative evolution was favorable. On postoperative day 3 patient presents intense abdominal pain and decreased hemoglobin. The CT shows subcapsular hepatic hematoma. Emergency surgery is performed for signs of hemorrhagic shock with evacuation of the hematoma and hemostasis. Postoperative evolution is good. There are several theories proposed for the occurrence of a subcapsular hematoma of the liver after laparoscopic cholecystectomy. Among these, the presence of a hemangioma, the use of NSAIDs or low molecular weight heparin. No clear mechanism is known and the only clinical sign can be abdominal pain. This case reminds us that we must take abdominal pain seriously after cholecystectomy in order to identify severe complications that can occur, such as hepatic subcapsular hematoma.
Single Semiconductor Nanostructure Extinction Spectroscopy

While emission-based, single-particle microscopies and spectroscopies have been highly successful in revealing the properties of matter hidden by ensemble averages, their limits have now become apparent. To address recognized future needs and, in particular, the need to go beyond fluorescent specimens, single-particle extinction techniques have been developed. Motivating this has been the desire to acquire information about the electronic structure of nanoscale materials difficult to obtain otherwise using either ensemble or emission-based, single-particle measurements. These techniques are, however, nontrivial since single nanostructures attenuate only 0.0001–1% of the incident light. This Review Article describes the challenges associated with overcoming the low signal-to-noise ratios inherent to low-dimensional semiconductor nanostructure extinction measurements. It simultaneously describes the fundamental operating principles and achievements of photothermal heterodyne imaging (PHI) and spatial modula.
Conceptualization and Situating of Sense of Belonging Among International Engineering Doctoral Students: In Light of the Previous Literature

Eunsil Lee is a Ph.D. candidate in Engineering Education Systems and Design program at Arizona State University (ASU) in the Fulton Schools of Engineering, The Polytechnic School. She earned a B.S. and M.S. in Clothing and Textiles from Yonsei University (South Korea) with the concentration area of Nanomaterials and Biomaterials in Textiles. She began her Ph.D. study in Textile Engineering but shifted her path toward Engineering Education a year later. Her research interests currently focus on engineering doctoral students in underserved populations such as women and international students.
STOCK PRICE TREND PREDICTION USING SUPPORT VECTOR MACHINE AND CORAL REEF OPTIMIZATION ALGORITHM

Due to non-linearity and non-stationary characteristics of stock market time series data, prior approaches have not been adequate enough for predicting stock market prices. Support vector machines are classifier that have been reported in the literature as having good recognition accuracy and have been applied in the area of predicting financial stock market prices and was found efficient. It is however noted that the performance of the SVM is affected by the values of the hyper-parameters used by the SVM. There is the need to find a way for searching for the best hyper-parameters that optimizes the performance of an SVM model. Coral Reef Optimization (CRO) is one of many nature-inspired algorithms used extensively to solve optimization problems. It is very effective in solving optimization problems because it is able to achieve global optimization. This paper’s contribution is the development of Coral Reef search algorithms for the improvement of the hyper-parameters of the SVM used for stock price trend prediction. The Algorithm is validated using stock data of two banks. The results obtained out-performed un-optimized SVM, and have the same performance as that of SVM optimized with the FireFly optimization algorithm.
Sensor Validation for Indoor Air Quality using Machine Learning

To guarantee a high indoor air quality is an increasingly important task. Sensors measure pollutants in the air and allow for monitoring and controlling air quality. However, all sensors are susceptible to failures, either permanent or transitory, that can yield incorrect readings. Automatically detecting such faulty readings is therefore crucial to guarantee sensors' reliability. In this paper we evaluate three Machine Learning algorithms applied to the task of classifying a single reading from a sensor as faulty or not, comparing them to standard statistical approaches. We show that all tested machine learning methods -- Multi-layer Perceptron, K-Nearest Neighbor and Random Forest -- outperform their statistical counterparts, both by allowing better separation boundaries and by allowing for the use of contextual information. We further show that this result does not depend on the amount of data, but ML methods are able to continue to improve as more data is made available.
Energy and industry 4.0: An application of ProKnow-C method

Industry 4.0 brings new challenges to the organizations and integrate energy management and its technologies are one of them. The possibility of real-time monitoring and more accurate data are some of the advantages of this integration. The present study aims to realize a literature review integrating the terms “energy” and “industry 4.0” to identify research gaps in the literature. The method used was ProKnow-C (Knowledge Development Process – Constructivist). As a result, a bibliographic portfolio of 26 articles was obtained and a bibliometric analysis was executed to identify year of publication, local of publication and the most used terms. Some of the literature gaps were identified like the intensive use of the Internet of Things and a lack of conceptual models that conciliate both themes.
Efﬁcient Task Adaptation with Normalization

Large pre-trained text encoders like BERT start a new chapter in natural language processing. A common practice to apply pre-trained encoders to sequence classiﬁcation tasks (e.g., classiﬁcation of sentences or sentence pairs) is by feeding the embedding of [CLS] token (in the last layer) to a task-speciﬁc classiﬁcation layer, and then ﬁne tune the model parameters of pre-trained model and classiﬁer jointly. In this paper, we conduct systematic analysis over several sequence classiﬁcation datasets to examine the embedding values of [CLS] to-ken before the ﬁne tuning phase, and present the imbalanced gradient issue—i.e., the gradient of some dimensions may be much larger than others and thus dominate the optimization process. This problem will lead to sub-optimal model performance since the model will over-focus on some features. To solve this problem, we heuristically propose several simple normalization methods, which forces the statistics (variance, gradient norm, etc.) to be similar in each dimension. In experiments, we ﬁnd that our proposed methods only boosts model performance on some datasets while do not work or even hurt the performance on others. We think our methods heavily depend on the embedding distribution. There is still much work to do in order to get a distribution-agnostic method.
A Fast Settling Multi-Standard CMOS Fractional-N Frequency Synthesizer for DECT/GSM/ CDMA &/NADC Wireless Communication Standards

A fast settling multi-standard CMOS fractional-N frequency synthesizer for DECT, GSM, CDMA and NADC wireless communication standards is proposed. This frequency synthesizer was simulated with ADS2008 in TSMC RF CMOS 0.18 µm. Frequency range is 824-1900 MHz, a switched capacitor LC-VCO was used in order to produce this frequency range. Frequency synthesizers have three main specifications of phase noise, settling time and power consumption. A new channel select circuit was designed instead of ∑∆ modulator to locate spur tones far from center frequency. A high reference frequency was used in order to reduce the VCO phase noise and locate the spur tones far from center frequency; these tones are produced by charge pump (reference spur) and N/N+1 divider (fractional spur). Two ways were used for phase noise optimization; in the first way phase noise was reduced by a low pass filter and a bypass capacitor (CT) that eliminate thermal noise and 2ω0 harmonics of tail current source; in the second way with biasing of VCO transistors only in saturation region preventing reduction of quality factor(Q) in tank circuit. These two ways in VCO of DECT were used, consequently the phase noise at 1875MHz center frequency was improved from -119.4 dBc/Hz at 3.4 MHz offset frequency to -144.3 dBc/Hz at 3.4 MHz offset frequency. The settling time for all standards was achieved less than almost 1 μs over the entire frequency range. For DECT synthesizer phase noise of -116.37 dBc/Hz at 3 MHz offset frequency was obtained, the first spur tone was located in 7.35 MHz offset from center frequency, also settling time of 350ns was obtained. The whole frequency synthesizer in loop1 (for DECT) draws 13 mA and in loop2 (for GSM900, CDMA & NADC) draws 13.67 mA from a 1.8 V voltage supply.
The Effect of Selected Chemical Preservatives and Starter Cultures on the Sensory Characteristics and Shelf Life of Rice Injera

Injera is yeast-risen flat bread with a unique, slightly spongy texture. It is a national staple in Ethiopia that is eaten daily in virtually every household. Rice injera has a very short life (2-3 days) at room temperature and essentially spoils due to mould growth. The use of weak organic acid as preservative is allowed in acidic foods, primarily as mould inhibitors. In this study, the effects of chemical preservatives: benzoic acid, sodium benzoate, and potassium sorbate and starter cultures (Lactobacillus plantarum+Saccharomyces cerevisiae) on the quality and shelf life of rice injera were investigated. Benzoic acid (0.1%), sodium benzoate (0.1%), potassium sorbate (0.2%) and a 1:1:1 blend of the three (0.2%) were added immediately before baking. Qualitative descriptive analysis (n=10) was used to describe the characteristics of the injera samples. A consumer acceptability panel (n=30) was used to determine the acceptability and shelf life of injera. The preservatives significantly (p<0.05) prolonged the shelf life of injera for up to 10 days with the combination of the three starters achieving the greatest effect. The findings of this study showed that the rice injera prepared with chemical preservatives (0.1 benzoic acid, 0.2% potassium sorbate, 0.1% sodium benzoate and 0.2% of the three preservatives retains maximum overall acceptability. Rice injera produced under controlled fermentation L. plantarum, and S. cerevisiae produce injera with better sensory quality than the traditional by using Irsho. Nine descriptors/attributes describing appearance, aroma/odor, taste, and texture were generated to characterize the sensory properties of rice injera. Softness, rollablity, fluffiness, eye size, whitness of top and bottom surfaces and slight sour taste are main characterstics descriptors of rice injera. Softness, fluffiness, spongness, slight sourness and eye size are attributes associated with quality of rice injera. Therefore, a starter combination of L. plantarum+S. cerevisiae together with 0.2% of the blend of the preservatives (0.1% benzoic acid+0.1% sodium sorbate+0.2% potassium sorbate) in 1:1:1 ratio preservatives can be used to produce acceptable injera with a shelf life of 10 days at room temperature.