Miracle-dz/UniFAR-FTUs huggingface dataset:
Blockchain based Data Sharing System for Supply Chain

— In this paper, we designed a consortium network based on permission blockchain to serve as secure data sharing system for supply chain. The design has the ability to provide data privacy among organization within the network. Organizations are able to share data only to specific group of organizations in the network that have been granted permission for accessing the data. The shared data are not accessible from any organizations outside the group. Data privacy is achieved by using network channel to define a group and its member. The obtained result proves that our proposed blockchain network design is successfully provides data privacy and data transparency among organization in the network.
Learning to Assign Credit in Reinforcement Learning by Incorporating Abstract Relations

Credit assignment is one of the most critical problems in re-inforcement learning to discover which actions are responsible for rewards. It becomes more serious as reinforcement learning is applied to real-world scenarios where the decision process may involve thousands of actions. In this paper, we propose a novel framework that utilizes a computation process to assign credits for hundreds of thousands of non-terminal state-action pairs, in order to accelerate the learning speed. Speciﬁcally, we ﬁrst abstract the states and actions of the original problem into a compact representation, which reduces the problem to a tractable size. Then, we solve the abstracted problem to obtain the optimal value function, which is the expected returns of future rewards. Finally, we use the derived value function to assign credits for state-action pairs of the original problem. We conduct extensive experiments on Doom, a complex 3D video game in which the reward signal is sparse. The experiment results demonstrate that our agent outperforms previous state-of-the-art agents in terms of both kill count and death number with a large margin. The effectiveness also manifests in an online competition of Doom, in which we achieved the 2nd place in the ﬁnal.
Electrostatic as well as hydrophobic interactions are important for the association of Cpn60 (groEL) with peptides

The interactions of groEL with five N-dansyl peptides were investigated by means of a fluorescence binding assay. The peptides studied (Bamph, Bhphil, Aamph, Ahphil, Namph) were designed and synthesised as systematic variants of each other in terms of their patterns of charge and hydrophobicity. Fluorescence data were analysed using a fluorescence modified, y-reciprocal linearised form of the Benesi–Hildebrand equation which was derived from first principles and verified by theoretical simulations. Under optimal conditions, apparent dissociation constants, Kd, were obtained in the µM range. At physiologically relevant ionic strengths, only two peptides (basic amphiphilic Bamph and neutral amphiphilic Namph) interacted with groEL whilst a third peptide (acidic amphiphilic Aamph) was able to interact but only at very high ionic strength (> 1 mol kg-1). Thermodynamic (van’t Hoff) analysis of the tightest binder, basic amphiphilic Bamph peptide, revealed endothermic binding and a large positive entropy, ΔSobind, consistent with a mixed binding mode involving both hydrophobic and electrostatic interactions. At physiologically relevant ionic strengths, positively charged amino acid residues appear to augment hydrophobic binding interactions with groEL by electrostatic attraction whilst negatively charged amino acid residues oppose short-range hydrophobic interactions with electrostatic repulsion. In conclusion, whilst a principal means of interaction between groEL and a peptide or partially folded protein substrate is certainly hydrophobic, electrostatic effects can modulate or even overwhelm this interaction.
Effect of micro-nutrients in anaerobic degradation of sulfate laden organics

The effect of micro-nutrients, such as Fe, Ni, Zn, Co, and Mo, on anaerobic degradation of sulfate laden organics was investigated using bench-scale models of upflow anaerobic sludge blanket (UASB) reactor, anaerobic baffled reactor (ABR), and hybrid anaerobic baffled reactor (HABR), operating in varying conditions in ten phases (organic loading of 1.9–5.75 kg COD/(m3·d), sulfate loading of 0.54–1.88 kg SO42–/(m3·d), chemical oxygen demand (COD):SO42– ratio of 2.0–8.6). In the initial phase, no nutrient limitation was observed with COD removal of more than 94% in all three systems. Subsequently, increase in sulfate loading resulted in Ni and Co limitation and their supplementation restored COD removal in UASB system. However, baffled systems did not recover because of severe inhibition by sulfide. Results indicate that precipitation of nutrients could seriously deteriorate process performance, leading to failure even before sulfide concentration attains toxic level. The limitation of Fe coupled with high .
Response of Some Vegetable Legume Plants to Foliar Application of Some Antioxidants

In this investigation, two field experiments were carried out at the experimental farm of Mallawy Agricultural Research Station, Minia, Egypt, during the two successive fall and winter seasons of 2012/2013 and 2013/2014, respectively. Phaseolus vulgaris cv. Nebraska and Pisum sativum cv. Master B, Vicia faba cv. Nubaria-1 (formely Giza Blanca) were used to study the influence of three antioxidants organic acids namely, Salicylic acid (SA), Vitamin E and Acetyl salicylic acid (ASA) on some yield characters, chemical constituents and antioxidative activities of total phenolic compounds (TPCs). Five concentrations i.e., 0.1, 0.5, 1.0, 2.0 and 4.0 mM were used from each antioxidant substance. Some physical properties and approximate analysis (dry matter DM, crude protein CP; crude fiber CF, crude lipids CL and ash content AC) were studied. The results indicate that the investigated legumes are rich and good sources of CP, CF and AC. Number of dry pods per plant, 100-seed weight and dry seeds yield of the three studied crops were significantly affected by using the antioxidant treatments. The best compound that gave, in average, the highest values was acetyl salicylic acid (ASA) at 1 mM concentration, on the other hand at 0.1 and 0.5 mM concentrations the highest value was obtained by using Vitamin E. The nitrite concentration (NO2 -1 mg/kg) in the three legumes ranged from 4.20 to 6.5 and did not reach toxic limit level (i.e. 10 mg/kg). The highest level of nitrite was recorded in Master B and the lowest one in Nebraska. These results meaning that the consumption of these vegetable legume seeds is save. All seed samples contain less than 200 mg NO3 -1 ion/kg and the highest concentration (155 mg/kg NO3 ion) was recorded in extracts of Master B and the lowest one in Nubaria 1. Concentrations of SA in legume seed samples were higher in all treatments compared with the untreated samples (control) and the uptake of SA differs according to the given doses. Changes in SA levels causing by spraying treatment was also studied and showed sharp increases in SA contents. The concentrations of TPCs and total flavonoids (TFs) in the crude extracts of whole seeds of the studied legumes were assayed and the results indicate that seeds of Nubaria-1 (dark coat seeds) contain higher levels of TPCs (8.3 mg/g) than those determined in seeds of Nebraska (7.4 mg/g) and much higher than Master B (6.5 mg/g) whereas, TFs concentration was the highest in extracts of Nebraska. [Wael. M. Abd El-Hakim. Response Of Some Vegetable Legume Plants To Foliar Application Of Some Antioxidants. World Rural Observ 2015;7(1):14-25]. ISSN: 1944-6543 (Print); ISSN: 1944-6551 (Online). http://www.sciencepub. net/rural. 3
A COMPARATIVE STUDY ON CLASSIFICATION ALGORITHMS FOR CREDIT CARD FRAUD DETECTION

The main problems within the credit card trade are ongoing a fraud. The credit card has made our life easy as we can pay easily and move without carrying any cash. Credit card gains its popularity and utilization has dramatically inflated in our day to day life, for the speedy advancement of electronic commerce technology. However, exploitation of credit card provides huge edges once used fastidiously and responsibly. Fraud activities are also increasing, and new techniques have been developed by criminals. Credit card and monetary damages are caused by fallacious activities. Such issues are tackled with Data Science, Machine Learning together with Deep Learning techniques, which cannot be exaggerated. This helps the bank and financial organizations, to detect the fraud at the early stage, and then they can reduce the ongoing fraud by not accepting the suspected transactions. The credit card company faces a huge loss if the cardholder does not detect the loss. An awfully very little quantity of data is needed by the assaulter for conducting any fallacious dealing in online transactions. During analysis work, numerous methods and outcome are reviewed, in terms of definite parameters.
Connectivity Re-establishment using Adjustable Sensor Nodes for Self-organization of Wireless Sensor Networks in the Presence of Dumb Nodes

In this work, we propose a scheme, named CoRAD , for the re-establishment of lost connectivity using adjustable communication range sensor nodes in the presence of dumb nodes in stationary wireless sensor networks (WSNs). A sensor node is termed as “dumb” [Misra et al. 2014], when it can sense its surroundings, but cannot communicate with its neighbors due to shrinkage in communication range attributed to adverse environmental effects such as rainfall, fog, and high temperature. These nodes behave normally following the resumption of favorable environmental conditions. Therefore, the presence of dumb nodes in a network gives rise to lost connectivity between the nodes, which are temporary in nature, and, thus, are distinct from the traditional isolation problem considered in stationary WSNs. The mere activation of intermediate sleep nodes cannot guarantee re-establishment of connectivity, because there may not exist neighbor nodes of the isolated nodes. On the contrary, the increase in communication range of a single sensor node may make it dead quickly. Including this, a sensor node has maximum limit of increase in communication range that may not be sufﬁcient to re-establish connectivity. Therefore, we propose a price-based scheme that helps the network to self-organize and re-connects the isolated nodes by activating some intermediate sleep nodes. The scheme increases the communication range of nodes, when there is no neighbor node in the reduced communication range. The scheme also deactivates the additional activated nodes and reduces the increased communication range, when the dumb nodes resume their normal behavior, on the return of favorable environmental conditions. To implement the proposed scheme CoRAD it is required to construct the network using GPS enabled adjustable communication range sensor nodes. Simulation results show that the proposed scheme exhibits improved performance over the existing topology management schemes such as LETC [Torkestani 2013], and A1 [Rizvi et al. 2012], in such scenarios with respect to the number of activated nodes, message overhead, and energy consumption.
On the Problems of CD Spectropolarimeter (IV) Artifacts Due to the Light Scattering by Small Particles

In three previous papers, we discussed in detail the artifacts which are observed in CD measurements with the use of commercially available CD spectrometers. The artifacts due to the imperfections of CD spectropolarimeter hardware were analyzed in the first paper. In the second paper, we investigated in detail possible artifacts resulting from the coupling of anisotropic samples and the imperfect optics and electronics of the CD spectrometer. The critical comments on liquid-crystal-induced circular dichroism were presented in the third paper. This note is a supplement to the discussion of artifacts in these papers, presented because we missed the CD artifact due to light scattering by small particles.
EMERGING SHARIA HOTEL IN INDONESIA: UNDERSTANDING THE TOURISTS’ MOTIVATION AND VALUES

The emergence of Halal Tourism is gaining attention both from managerial and academic aspects. Several countries develop Halal Tourism to attract a large number of Muslim tourists. However, there is a limited research investigating the potential of Sharia Hotel from the consumers’ perspective. The purpose of this study is to gain understanding of tourist’s motivation and values to choose and stay in Sharia Hotel. An indepth interview with three hotel managers and 18 visitors at Sharia Hotel in Yogyakarta and Solo, Indonesia was conducted. The results of the study found that there are three groups of tourists staying at Sharia Hotel. The first group was people who are motivated by seeking for novelty experience who put high importance on freedom and fun. The second group was people who are driven by benefits maximization that consider hotel’s functional attributes (i.e., price, place, comfort). The third group was people who choose Sharia as “the way of life”. They committed to Sharia principles in all aspects of their daily life. The study concluded with managerial implications and directions for further research.
Identifying Sequential Complication and Mortality Patterns in Diabetes Mellitus: Comparisons of Machine Learning Methodologies

Background: Diabetes mellitus-related complications adversely affect the quality of life. Better risk-stratified care through mining of sequential complication patterns is needed to enable early detection and prevention. Methods: Univariable and multivariate logistic regression was used to identify significant variables that can predict mortality. A sequence analysis method termed Prefixspan was applied to identify the most common couple, triple, quadruple, quintuple and sextuple sequential complication patterns in the directed comorbidity pathology network. A knowledge enhanced CPT+ (KCPT+) sequence prediction model is developed to predict the next possible outcome along the progression trajectories of diabetes-related complications. Findings: A total of 14,144 diabetic patients (51% males) were included. Acute myocardial infarction (AMI) without known ischaemic heart disease (IHD) (odds ratio [OR]: 2.8, 95% CI: [2.3, 3.4]), peripheral vascular disease (OR: 2.3, 95% CI: [1.9, 2.8]), dementia (OR: 2.1, 95% CI: [1.8, 2.4]), and IHD with AMI (OR: 2.4, 95% CI: [2.1, 2.6]) are the most important multivariate predictors of mortality. KCPT+ shows high accuracy in predicting mortality (F1 score 0.90, ACU 0.88), osteoporosis (F1 score 0.86, AUC 0.82), ophthalmological complications (F1 score 0.82, AUC 0.82), IHD with AMI (F1 score 0.81, AUC 0.85) and neurological complications (F1 score 0.81, AUC 0.83) with a particular prior complication sequence. Interpretation: Sequence analysis identifies the most common pattern characteristics of disease-related complications efficiently. The proposed sequence prediction model is accurate and enables clinicians to diagnose the next complication earlier, provide better risk-stratified care, and devise efficient treatment strategies for diabetes mellitus patients.
HDR Denoising and Deblurring by Learning Spatio-temporal Distortion Models

We seek to reconstruct sharp and noise-free high-dynamic range (HDR) video from a dual-exposure sensor that records different low-dynamic range (LDR) information in different pixel columns: Odd columns provide low-exposure, sharp, but noisy information; even columns complement this with less noisy, high-exposure, but motion-blurred data. Previous LDR work learns to deblur and denoise (DISTORTED->CLEAN) supervised by pairs of CLEAN and DISTORTED images. Regrettably, capturing DISTORTED sensor readings is time-consuming; as well, there is a lack of CLEAN HDR videos. We suggest a method to overcome those two limitations. First, we learn a different function instead: CLEAN->DISTORTED, which generates samples containing correlated pixel noise, and row and column noise, as well as motion blur from a low number of CLEAN sensor readings. Second, as there is not enough CLEAN HDR video available, we devise a method to learn from LDR video in-stead. Our approach compares favorably to several strong baselines, and can boost existing methods when they are re-trained on our data. Combined with spatial and temporal super-resolution, it enables applications such as re-lighting with low noise or blur.
Taking Principles Seriously: A Hybrid Approach to Value Alignment

An important step in the development of value alignment (VA) systems in artificial intelligence (AI) is understanding how VA can reflect valid ethical principles. We propose that designers of VA systems incorporate ethics by utilizing a hybrid approach in which both ethical reasoning and empirical observation play a role. This, we argue, avoids committing “naturalistic fallacy,” which is an attempt to derive “ought” from “is,” and it provides a more adequate form of ethical reasoning when the fallacy is not committed. Using quantified model logic, we precisely formulate principles derived from deontological ethics and show how they imply particular “test propositions” for any given action plan in an AI rule base. The action plan is ethical only if the test proposition is empirically true, a judgment that is made on the basis of empirical VA. This permits empirical VA to integrate seamlessly with independently justified ethical principles. This article is part of the special track on AI and Society.
Tractable Orders for Direct Access to Ranked Answers of Conjunctive Queries

We study the question of when we can provide logarithmic-time direct access to the k-th answer to a Conjunctive Query (CQ) with a specified ordering over the answers, following a preprocessing step that constructs a data structure in time quasilinear in the size of the database. Specifically, we embark on the challenge of identifying the tractable answer orderings that allow for ranked direct access with such complexity guarantees. We begin with lexicographic orderings and give a decidable characterization (under conventional complexity assumptions) of the class of tractable lexicographic orderings for every CQ without self-joins. We then continue to the more general orderings by the sum of attribute weights and show for it that ranked direct access is tractable only in trivial cases. Hence, to better understand the computational challenge at hand, we consider the more modest task of providing access to only a single answer (i.e., finding the answer at a given position) - a task that we refer to as the selection problem. We indeed achieve a quasilinear-time algorithm for a subset of the class of full CQs without self-joins, by adopting a solution of Frederickson and Johnson to the classic problem of selection over sorted matrices. We further prove that none of the other queries in this class admit such an algorithm.
Near Infrared Reflectance Spectroscopy for Online Particle Size Analysis of Powders and Ground Materials

The cross-sensitivity of near infrared (NIR) reflectance to the particle size of powders or ground materials has long been documented but not fully exploited for particle size estimation. Diffuse reflectance of a powder sample is dependent on light scattering within its layers, and a powder's absorption and scattering coefficient are related to its particle size. This is the basis of NIR reflectance–particle size calibrations. The availability of fibre optic probes and the speed of NIR spectrometers make them suitable for remote and online sensing of particle size, in addition to providing chemical information of a powder sample. The basics of NIR reflectance spectroscopy relevant to particle size determination and its relation to sample preparations, methods of presentation, reference methods, calibration development and validation are reviewed in this paper.
Applying wav2vec2.0 to Speech Recognition in various low-resource languages

There are several domains that own corresponding widely used feature extractors, such as ResNet, BERT, and GPT-x. These models are usually pre-trained on large amounts of unlabeled data by self-supervision and can be effectively applied to downstream tasks. In the speech domain, wav2vec2.0 starts to show its powerful representation ability and feasibility of ultra-low resource speech recognition on the Librispeech corpus, which belongs to the audiobook domain. However, wav2vec2.0 has not been examined on real spoken scenarios and languages other than English. To verify its universality over languages, we apply pre-trained models to solve low-resource speech recognition tasks in various spoken languages. We achieve more than 20% relative improvements in six languages compared with previous work. Among these languages, English achieves a gain of 52.4%. Moreover, using coarse-grained modeling units, such as subword or character, achieves better results than fine-grained modeling units, such as phone or letter.
Investigations with Spectroscopy, Zeta Potential and Molecular Modeling of the Non-Cooperative Behaviour Between Cyclophosphamide Hydrochloride and Aspirin upon Interaction with Human Serum Albumin: Binary and Ternary Systems from the View Point of Multi-Drug Therapy

Abstract The interaction between cyclophosphamide hydrochloride (CYC) and aspirin (ASA) with human serum albumin (HSA) was studied by various kind of spectroscopic, ζ potential and molecular modeling under physiological conditions. The fluorescence data showed that the binding of drugs to proteins caused strong static fluorescence quenching. The analysis of the fluorescence quenching of HSA in the binary and ternary systems displayed that ASA was affected by the complex formed between CYC and HSA. Moreover, CYC was influenced by the HSA-ASA complex. The inherent binding information, including the quenching mechanism, binding constants, number of binding sites, effective quenching constant, fraction of the initial fluorescence and thermodynamic parameters were measured by the fluorescence quenching technique at various temperatures. In addition, according to the synchronous fluorescence spectra of HSA, the results showed that the fluorescence quenching of HSA originated from the Trp and Tyr residues, and indicated a conformational change of HSA with the addition of the drugs. Far-UV CD spectra of HSA were recorded before and after the addition of ASA and CYC as binary and ternary systems. An increase in intensity of the positive CD peak of HSA was observed in the presence of the drugs. The results were interpreted by excited interactions between the aromatic residues of the HSA binding sites and the drugs bound to them. The distance r between donor and acceptor was obtained by the Förster energy according to fluorescence resonance energy transfer (FRET) and found to be 2.35 nm and 1.78 nm for CYC and ASA, respectively. This confirmed the existence of static quenching for proteins in the presence of CYC and ASA. Furthermore, docking studies pointed at a reduction of the affinity of each of the drug compounds to the protein in the presence of the other in meaningful amounts. Pre-binding of any of the said compounds forced the second to bind in a non-optimized location and orientation. The potential at the electrokinetic shear surface of the protein-drug solution were measured at several concentrations of the drugs by the ζ potential technique, which confirmed experimental and theoretical results.