Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Models for Non-Uniformly Sampled Data

Despite the unquestionable success of deep learning models in solving various machine learning problems, they are generally limited to achieving acceptable performance only on highly structured data, such as images or natural language data. One key limitation is that most of these models either cannot handle non-uniformly sampled data or work poorly on it. However, in some areas, like environmental and medical research, the modelled data typically does not reside on a grid, nor is it uniformly sampled. This problem has attracted a lot of attention from the machine learning community lately, and several of successful approaches have been proposed. However, coming from different machine learning domains, such as unsupervised generative modelling and few-shot learning, these approaches lack unified perspective. This perspective is desirable as it could provide a rigorous description of the emerging field of off-the-grid time series modelling. This work develops a unifying framework for models capable of handling irregularly-spaced time series data. In this work, we consider various models proposed within both unsupervised learning and meta-learning paradigms. Within these paradigms, we are concerned with a wide range of models, from entirely non-amortised to fully amortised ones. We come up with a series of schematics that place this considerable variability of models from disjoint machine learning domains into a common context. These schematics could be beneficial in comprehending the general approaches to data modelling as well as in choosing the appropriate model for a particular task setting. Our qualitative and quantitative evaluation of several models from the proposed framework provides further observational insights as to which model should be used in which setting. Finally, within the proposed unifying framework, we naturally encountered novel models operating within the meta-learning framework. These models ideally fit in the considered schematics and could be applied to various few-shot learning tasks involving time-series data.
Segmentation of Ultrasound Images Using Closest Neighbour Approach

-As we know image segmentation is field which is uses in automated recognition of objects in medical fields, traffic analysis, face recognition and many more. In past few year as image processing goes on hike researches continuously exploring the field of image segmentation with various algorithm. Main problem of this field is overcome from over segmentation and the merging criteria for various clusters to segment an object. Medical images are difficult to segment due to low contrast and speckle noise. We are going to overcome over segmentation and will use closest element approach to merge various objects for segmentation. Also compare it with other technique of segmentation.
PREVALENCE OF DENTAL CARIES AMONG SCHOOL GOING CHILDREN TWELVE TO FIFTEEN YEARS OF PESHAWAR CITY

Objective: To determine the prevalence of dental caries and to calculate the average DMFT score of school-going children (12-15 years). To compare age, gender and socioeconomic status with the DMFT score. Materials and Methods: A cross-sectional study was conducted in school-going children aged 12-15 years Of Peshawar city (Hayatabad). The sample size was 500 students, which was calculated by WHO formula N=z2 x P (1 – P)/ d2. The inclusion criteria were students age 12-15 years, and only those schools offering matriculate system were included. All the schools offering the Cambridge system and students below 12 years and above 15 years were excluded. Results: The results of the current study reveal that the prevalence of dental caries of school-going children 12-15 years was 71%. The average DMFT score of the sample was 2.61. Among the different age groups, 15 years old children had the highest DMFT score of 3.7. The DMFT score of females, i.e., 2.57, was found more than the DMFT of males, i.e., 1.77. The medium socioeconomic class showed the highest, i.e., DMFT scores i.e., 3.1. The data collected were analyzed and tested for significance using statistical software package, SPSS software for windows (version 19.0). Conclusion: The study shows a very high prevalence of 71%, which was highest in 15-year-old children. Females were more affected than males. Children belonging to the middle and lower class were more affected than the children of the high socioeconomic group.
Changing Social Norms

The use of social sanctions against behaviour which contradicts a set of informal rules is often an important element in the functioning of informal institutions in traditional societies. In the social sciences, sanctioning behaviour has often been explained in terms of the internalisation of norms that prescribe the sanctions (e.g. Parsons 1951) or the threat of new sanctions against those who do not follow sanctioning behaviour (e.g. Akerlof 1976). We present an alternative to these theories, that offers insights about the persistence of social norms and the manner in which they may evolve. Our underlying assumption is that people derive utility from ostracising those who they believe to have ’bad character’but there is uncertainty and learning about how the character of a person may be inferred. Using this framework, we can account for both social norms that persist for long periods and unravel suddenly and those that evolve gradually over time. We apply the model to explain the phenomenon of persistent low labour market participation of women in Bangladesh. JEL Codes: D01, D02, D83, Z10 ∗z.wahhaj@kent.ac. uk. School of Economics, Keynes College, University of Kent, Canterbury CT2 7NP, United Kingdom
Information-Theoretic Exploration with Successor Uncertainties

The exploration and exploitation trade-off dilemma has been at the heart of the reinforcement learning research community for a very long time. In recent years, the SU algorithm was created which achieved impressive results on hard tabular benchmarks and on the Atari 2600 domain. In this thesis we extend the original SU model by incorporating a secondary Q-function that accounts for the information gain which we use in a linear combination with the Q-function of the SU model to perform action selection. Based on this informationtheoretic approach we propose two algorithms SU-IG1 and SU-IG2 respectively. We conduct experiments on these methods in the binary tree MDP environment where we find out that both algorithms manage to solve the binary tree MDP consistently achieving similar performance to that of the original SU model.
The Annals of the University Dunarea de Jos of Galati

This study aimed at assessing the ability of the foodborne pathogenic bacterium Listeria monocytogenes to resist high pressure processing when present in cucumber juice and evaluating its capacity to recover during post-processing storage at 8°C for 72 hours. Two L. monocytogenes strains were selected, Scott A and RO15, a reference and a food isolated strains, respectively. The cucumber juice was inoculated with either Scott A or RO15 strain at a concentration of approximately 7 log CFU/mL and treated at 300 and 400 MPa, 8°C, for 8 minutes. The behavior of L. monocytogenes populations was studied by employing both quantitative and qualitative approaches: enumeration of L. monocytogenes viable cells by plate counting on a selective growth medium and measuring the fluorescence intensity emitted by the cells when stained with propidium iodide (PI). The treatment at 300 MPa, 8°C, for 8 minutes determined a reduction rate of less than 1 log CFU/mL for both L. monocytogenes strains, while treatment at 400 MPa led to a significantly higher reduction in cells number, 6 and 5 log CFU/mL for Scott A and RO15 strain, respectively. L. monocytogenes viable cells counting at each time point (0, 24, 48 and 72 hours) revealed no multiplication of survivors during storage at 8°C. However, the fluorescence method suggested a possible cellular membrane recovery process, since fluorescence intensity emitted by the HP treated L. monocytogenes cells decreased continuously over the storage period compared to time 0. The results of this experiment emphasize the necessity of employing other barriers against L. monocytogenes in combination with HPP, to ensure its consumption safety during storage for periods longer than 72 hours.
The Nicotinic Acetylcholine Receptor Subunit α5 Mediates Short-Term Effects of Nicotine in Vivo

Nicotine, acting at pentameric neuronal nicotinic acetylcholine receptors (nAChRs), is the primary addictive component in tobacco. At low doses, it affects attention, learning, memory, anxiety, cardiovascular responses, thermoregulation, and nociception. At high doses, nicotine produces more drastic behaviors and eventually induces tonic-clonic seizures in rodents. In mammals, several subunits of the nAChRs have been cloned, including eight α and three β subunits. To study the physiological role of the α5 subunit, we have generated α5-deficient mice. These mice have a generally healthy appearance and are normal in a standard battery of behavioral tests. However, the sensitivity of α5 mutant mice to nicotine-induced behaviors and seizures is dramatically reduced compared with their wild-type littermates. These animals have a normal brain anatomy and normal levels of mRNA for other nAChR subunits, namely α4, α6, α7, β2, and β4. In addition, 125I-epibatidine and [125I]α-bungarotoxin binding in the brains of α5-deficient mice is normal. Together, these results suggest a direct involvement of the α5 subunit in the observed phenotypes.
Does Genetic Distance have a Barrier Effect on Technology Diffusion? Evidence from Historical China

Using the distribution of surnames during 960-1368 to proxy for the distribution of alleles at locus a millennium ago, we construct a unique measure of genetic distance of the ethnic Han between pairs of Chinese prefectures. Taking the adoption of maize and the steam engine in historical China as examples, and employing the differences in assimilation with the Han between two nomadic groups forcibly resettled by the Mongol Empire as instrument, we find that genetic distance has a significant short-run barrier effect on the probability of technology diffusion. Specifically, it affects technology diffusion likely through the channel of interaction.
Process Modelling, Thermodynamic Analysis and Optimization of Dry Reforming, Partial Oxidation and Auto-Thermal Methane Reforming for Hydrogen and Syngas production

Abstract In this work, process modelling, thermodynamic analysis and optimization of stand-alone dry and partial oxidation reforming of methane as well as, the auto-thermal reforming processes were investigated. Firstly, flowsheet models were developed for both the stand-alone systems and auto-thermal reforming process using ASPEN HYSYS®. Furthermore, thermodynamic studies were conducted for the stand-alone and auto-thermal reforming processes for temperatures range of 200–1000°C and pressure range of 1–3 bar using Gibbs free energy minimization methods which was also performed using ASPEN HYSYS®. The simulation of the auto-thermal reforming process was also performed at 20 bar to mimic industrial process. Process parameters were optimized in the combined reforming process for hydrogen production using desirability function. The simulation results show that 84.60 kg/h, 62.08 kg/h and 154.7 kg/h of syngas were produced from 144 kg/h, 113 kg/h and 211 kg/h of the gas fed into the Gibbs reactor at CH4/CO2/O2 ratio 1:1:1 for the stand-alone dry reforming, partial oxidation reforming and auto-thermal processes respectively. Equilibrium conversion of CH4, CO2, O2 were thermodynamically favoured between 400 and 800°C with highest conversions of 100%, 95.9% and 86.7% for O2, CO2 and CH4 respectively. Highest yield of 99% for H2 and 40% for CO at 800°C was obtained. The optimum conditions for hydrogen production were obtained at CH4/CO2, CH4/O2 ratios of 0.634, 0.454 and temperature of 800°C respectively. The results obtained in this study corroborate experimental studies conducted on auto-thermal reforming of methane for hydrogen and syngas production.
Fruit and seed biometry of Carpotroche brasiliensis (RB) A. Gray (Achariaceae), a tropical tree with great potential to provide natural forest products

Carpotroche brasiliensis (RB) A. Gray (Achariaceae) is a native tree species of the Brazilian Atlantic Forest with great potential provide natural forest products in agroforestry systems. The oil of its seeds contains medicinal and cosmetic properties, and the fruits are appreciated by wild animals. In this study, we analyzed the biometry of fruits and seeds collected from naturally-grown trees in agroforestry systems on small farms in southern Bahia, Brazil. Fresh fruit mass (FFM), fruit length (FL), fruit diameter (FD), number of seeds per fruit (NSF), total fresh seed mass per fruit (FSMF), total dry mass of seeds per fruit (DMSF), and mass of 1,000 seeds (MTS) were collected from 66 fruits of 18 trees on six rural properties. Seed length (SL) and seed diameter (SD) were also evaluated for 5335 seeds. From this sample universe, 697 seeds represented an adequate sample size to measure these dimensions with statistical precision. The fruits analyzed in this study had uniform values for most of the biometric variables among the sites. The average values of NSF, FFM, and MTS were approximately 88 seeds, 0.5 kg, and 1.3 kg, respectively. Seeds of C. brasiliensis obtained from freshly-harvested fruits had high water content, with an average of more than 45%. Strongly significant correlations between FFM and FD and between FMSF and DMSF indicate the possibility of developing simple procedures to estimate seed production for commercial purposes from field evaluations.
DOCTORAL THESIS

We studied nucleation in progressively more abstract contexts and systems, starting from classical nucleation theory and ending with nucleation in complex networks. The cases studied include impurity nucleation in a solid matrix on several alkali halide crystals, where we determined formation energies for clusters, treated as defects, starting from single impurity-vacancy dipole and small aggregates to possible configurations of larger clusters. In the next part, we turn to the study of heterogeneous nucleation. While in the usual treatment of heterogeneous nucleation the surface energy is assumed to be homogenous, we ask the question what happens if we consider the surface energy to be heterogeneous. Utilizing umbrella sampling computer simulations we find the nucleation barrier can be significantly lowered in the presence of surface heterogeneity, even if the average surface energy is kept constant. In the last part we study influence of clustering coefficient on phase transitions in scale-free networks, using forward flux sampling (FFS).
Effect of elevated CO2 and temperature on growth and yield of wheat grown in sub-humid climate of eastern Indo-Gangetic Plain (IGP)

The atmospheric CO2 will be in the range of 510 to 760 L-1 by the end of 21st century and mean global temperature will be 1.5 to 4.5 oC higher than the present day which has a direct and indirect effect on agriculture. India is a key global region vulnerable to climate change; however, limited studies have focused on the combine effect of CO2 enrichment and temperature on wheat production in Sub-humid climate of eastern IGP in India. To address this issue, an Open top chamber (OTCs) experiment was conducted during 2013-14, to determine the effects of elevated atmospheric carbon dioxide (CO2) and temperature on growth, yield attributes and yield of wheat. Wheat cultivars (DBW 14 and HD 2967) were grown with four treatment combination of CO2 and temperature in OTCs, during the rabi season. The study revealed that wheat genotypes performed better under elevated CO2 condition in term of grain number, test weight and grain yield than an ambient condition. The greater biomass under elevated CO2 was brought about by an increase in radiation use efficiency (RUE) during both heading and physiological maturity periods. Elevated temperature decreased the grain yield but increase plant height compared to ambient temperature. Days to physiological maturity was reduced by 4 to 7 days in both the cultivars under elevated temperature condition and increased by 3 to 4 days under the elevated CO2 condition with respect to ambient condition. The elevated CO2 had positive effects whereas elevated temperature had negative effects on growth, yield attributes and yield of wheat. With elevation of both CO2 and temperature, elevated CO2 compensate the negative effects of elevated temperature on growth, yield attributes and yield of wheat.
FPGA Implementation of Bluetooth Low Energy Beacon-Based Indoor Positioning System

 Abstract —In this paper, we described the field programmable gate array (FPGA) implementation of Bluetooth Low Energy (BLE) beacon-based indoor positioning system. Indoor positioning system relies on received signal strength indication (RSSI) from indoor wireless devices. The accuracy of indoor positioning system is easily affected by several signal interference. In order to correct for unstable RSSI values, Kalman filtering technique that has faster and lower error rate is adapted in this system. Also, we adopted the improved trilateration algorithm that has an error range of less than 0.5 m. This system was implemented using Intel's FPGA design tools Quartus II on DE1-SoC board.
GoCo: A Gamiﬁed Activity for Winnowing Visualization Projects with Interdisciplinary Experts

Interdisciplinary collaboration in an academic context is challenging, particularly when the basis of collaboration is data. Even with datasets that overlap in their spatiotemporal dimensions, underlying disciplinary assumptions may not allow it to be meaningfully synthesized without thorough alignment among its experts. We encountered this issue while tasked to develop a visualization that combined data from different disciplines. The breadth of possibilities within these interdisciplinary settings meant that winnowing was needed to align all experts before further process could be made. We therefore designed and deployed a winnowing technique speciﬁcally apt for multi-disciplinary settings. Our design, GoCo, a hybrid sys-tem consisting of a tangible and digital counterparts, uses abstract concepts, playfulness, gamiﬁcation and network visualizations, to uncover promising research directions. Through ﬁndings from its deployment, we believe this work informs early stage visualization activity practices on aspects of gamiﬁcation, tangible tokens and hybrid documentation 1 .
Fabrication of bi-modal nanoporous bimetallic Pt–Au alloy with excellent electrocatalytic performance towards formic acid oxidation

In the present work, a green and simple strategy has been proposed to fabricate novel bi-modal nanoporous bimetallic Pt–Au alloy by electrochemical dealloying of a ternary Al75Pt15Au10 precursor in a neutral sodium chloride solution. The Al75Pt15Au10 precursor is composed of a single Al2(Pt,Au) phase with lattice vacancies inside. The bi-modal nanoporous Pt–Au alloy exhibits an island-channel structure and the islands show an ultrafine three-dimensional bicontinuous interpenetrating ligament-channel (∼3.5 nm) characteristic. The dealloying mechanism of the precursor and the formation of the nanoporous structure have been addressed using electrochemical measurements (potentiodynamic and potentiostatic polarization) and microstructural analysis (scanning electron microscopy, transmission electron microscopy and energy dispersive X-ray analysis). The dealloying at the low potential of −0.4 V vs.Ag/AgCl is associated with the partial dissolution of Al and the disappearance of the vacancies, leading to the formation of the stoichiometric Al2(Pt,Au). The subsequent dealloying at 0.6 V vs.Ag/AgCl is related to the complete dissolution of Al and surface diffusion of Pt/Au, resulting in the formation of the ultrafine nanoporous structure. Besides, the bi-modal nanoporous Pt–Au alloy shows superior catalytic activity towards the electro-oxidation of formic acid in the acid media in comparison to the commercial JM-Pt/C catalyst. Our present findings provide implications for green synthesis of novel multi-functional nanoporous alloys through the electrochemical dealloying strategy in benign neutral salt solutions under mild conditions.
Prediction of type 1 diabetes at birth: cord blood metabolites versus genetic risk score in the MoBa cohort.

Background and aim Genetic markers are established as predictive of type 1 diabetes, but unknown early life environment is believed to be involved. Umbilical cord blood may reflect perinatal metabolism and exposures. We studied whether selected polar metabolites in cord blood contribute to prediction of type 1 diabetes. Methods Using a targeted UHPLC-QQQ-MS platform, we quantified 27 low molecular weight metabolites (including amino acids, small organic acids and bile acids) in 166 children, who later developed type 1 diabetes, and 177 random control children in the Norwegian Mother, Father and Child (MoBa) cohort. We analysed the data using logistic regression (estimating odds ratios per standard deviation [aOR]), area under the receiver operating characteristic curve (AUC) and k-means clustering. Metabolites were compared to a genetic risk score based on 51 established non-HLA SNPs, and a four-category HLA risk group. Results The strongest associations for metabolites were aminoadipic acid (aOR=1.23,95%CI:0.97-1.55), indoxyl sulfate (aOR=1.15,95%CI:0.87-1.51), and tryptophan (aOR=0.84,95%CI:0.65-1.10), with other aORs close to 1.0, and none significantly associated with type 1 diabetes. K-means clustering identified six clusters, none of which were associated with type 1 diabetes. Cross-validated AUC showed no predictive value of metabolites (AUC 0.49), while the non-HLA genetic risk score AUC was 0.56 and the HLA risk group AUC was 0.78. Conclusions In this large study, we found no support of a predictive role of cord blood concentrations of selected bile acids and other small polar metabolites in the development of type 1 diabetes.
A practical method for assessing cadmium levels in soil using the DTPA extraction technique with graphite furnace analysis

Abstract Using the DTPA extraction procedure and a graphite furnace atomic absorption spectrophotometer, a practical method for determining soil cadmium levels was developed. Furnace parameters, instrument parameters, solvent dilution factor, and solvent characteristics were determined using experimental field samples and standardized control samples. The DTPA extraction method gave reproducible results and removed approximately 20 to 60% of total soil cadmium.
ABTS•+ scavenging activity of polypyrrole, polyaniline and poly(3,4‐ethylenedioxythiophene)

Although many methods are available for the evaluation of the antioxidant capacity of samples presented in the liquid state, typically food and beverages, to date only the 2,2′-diphenyl-1-picrylhydrazyl (DPPH) assay has been applied to the measurement of the antioxidant capacity of solid samples such as active packaging materials. A modified 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) assay has been successfully developed for the measurement of the antioxidant capacity of conducting polymer powders. The ABTS•+ radical scavenging activity of polypyrrole (PPy), polyaniline (PANI) and poly(3,4-ethylenedioxythiophene) (PEDOT) powders was compared. The ranking order for greatest antioxidant capacity among the conducing polymer powders was PANI > PPy > PEDOT. The reduced forms of all the three conducting polymer samples were found to show greater radical scavenging activity than their as-prepared partially oxidized forms. The modified ABTS assay is a simple, rapid and sensitive method for evaluating the antioxidant capacity of conducting polymer powders. The method is also suitable for composite antioxidant materials comprising a conducting polymer and a conventional packaging polymer. Copyright © 2010 Society of Chemical Industry