Miracle-dz/UniFAR-FTUs huggingface dataset:
EXTRACTION OF AGAR FROM Gelidium P (RHODOPHYTA) AND GREEN SYNTHESIS OF AGAR /SILVER NANOPARTICLES

Physicochemical and rheological characters of agar sample extracted from(rhodophyta)Gelidium sp. collected from the Egyptian coast of the red sea has been investigated. Agar yielded 29% on dry biomass basiswith pretreatment using 0.15 M sodium hydroxide. Agar surface texture was investigated through the usage of the scanning electron microscopy (SEM). Agar is a white flakes and threads, insoluble in cold water, but it swells absorbing much water making hydrogels.The morphology of the agar surface texture was investigated using scanning electron microscopy (SeM). The dynamic rheological measurements of agar solutions (2, 3, 4 mg agar/ml) as a function of shear rate were achieved at 85o C and let to cool gradually (1.5oC/ min), with the maximum values of viscosity as following 1.26, 3.12 and 5.18cP, respectively at shear rate of 40 sec-1.Agr solutions revieled the presence of non-Newtonian fluid material demonstrating shear thinning (Pseudoplastic) flow behavior in aqueous solution (2 mg agar/ml) giving up to formation of an elastic gel. At higher concentrations (3 & 4 mg agar/ml) induce shear thickening representd as viscosity increases as shear rate increased giving up to Newtonian fluid behavior.The AgNPs were synthesized and characterized on the bases of spectral (FT-IR and UV-visible), morphological (Transmission electron microscopy-TEM), zeta potential and atomic force microscopy (AFM) measurements. The resulted Agar Nanoparticles (AgNPs) are showing gradualproperities as gradual increase in absorbance with increasing the intensity of the yellow-brown color, it showed peak maximum located at 410 nm with absorbance value of 0.579. The average size distributions of AgNPs were found to be . It was illustrated that zeta potential value for AgNPs was -28.0 mV.
Cyber-Physical System Architecture for Minimizing the Possibility of Producing Bad Products in a Manufacturing System

Additional information is available at the end of the chapter Abstract The new industry 4.0 requires the implementation of several cyber-physical systems to increase the level of productivity in a manufacturing system. This chapter propos‐ es an architecture of a generic manufacturing system that requires the use of techni‐ ques of agile production, lean manufacturing, and statistical approaches. The combination of the previous techniques will be implemented in the architecture pro‐ posed for minimizing the possibility of producing bad products. Thus, the cyber-physical system architecture proposed will optimize the overall system thanks to the implementation of intelligent modules and control strategies. Moreover, 10 proposed actions will be described in detail. These actions can be implemented in cyber-physi‐ cal systems that take into account five levels.
CHIRRUP: a practical algorithm for unsourced multiple access

Unsourced multiple access abstracts grantless simultaneous communication of a large number of devices (messages) each of which transmits (is transmitted) infrequently. It provides a model for machine-to-machine communication in the Internet of Things, including the special case of radio-frequency identification, as well as neighbour discovery in ad hoc wireless networks. This paper presents a fast algorithm for unsourced multiple access that scales to ${\mathscr{C}}=2^{100}$ (active or non-active) devices (arbitrary $100$ bit messages). The primary building block is multiuser detection of binary chirps, which are simply codewords in the second-order Reed–Muller code. The chirp detection algorithm originally presented by Howard et al. (2008, 42nd Annual Conference on Information Sciences and Systems) is enhanced and integrated into a peeling decoder designed for a patching and slotting framework. In terms of both energy per bit and number of active devices (number of transmitted messages), the proposed algorithm is within a factor of $2$ of state-of-the-art approaches. A significant advantage of our algorithm is its computational efficiency. We prove that the worst-case complexity of the basic chirp reconstruction algorithm is ${\mathscr{O}}[nK(\log _2^2 n + K)]$, where $n$ is the codeword length and $K$ is the number of active users. Crucially, the complexity is sublinear in ${\mathscr{C}}$, which makes the reconstruction computationally feasible—a claim we support by reporting computing times for our algorithm. Our performance and computing time results represent a benchmark against which other practical algorithms can be measured.
A virtual internship for developing technological pedagogical content knowledge

This study examines the use of a virtual internship (an epistemic game) for developing preservice teachers’ technological pedagogical content knowledge (TPACK). TPACK aims to capture the essential qualities of teacher knowledge that are needed for integrating technology into teaching. Virtual internships are computer-based professional practicum simulation games where participants assume the role of a professional, work collaboratively on authentic tasks, and engage in complex professional thinking. The online collaborative chat records of 33 preservice teachers who played the game over the course of 8 weeks were analysed using epistemic network analysis (ENA), which made it possible to examine the dynamic connections between various TPACK domains over time. The analysis showed that participants’ TPACK representations gradually became more complex in terms of the number of pedagogical considerations and the strength of connections between pedagogical considerations, technology, and content. Suggestions are made for designing learning environments that aim to develop preservice teachers’ TPACK.
Agent Based Decision Support System for Healthcare Applications

A healthy nation is a wealthy nation. Healthcare, being a universal area, concerns itself with the entire humanity. Healthcare, as an industry, will continue to grow and thrive as long as humans exist hence forming a large part of any countrys economy. In this context, the two most important domains are epidemics and healthcare coverage. The role of public healthcare facilities in both these domains is extensive. In this work, we introduce the application modules of an indigenously built tool used to simulate dynamic movement in a multi-agent based environment having complex social interactions. This work uses the tool to show it can be used in healthcare to perform probabilistic analysis effectively. During an epidemic outbreak, strategic deployment of healthcare resources, which are usually limited in number, is very critical. In this work, dynamic health care units are used to represent those dynamic resources which can travel among cities and cure a fraction of the infected population. We have developed a tool based on agent based approach that effectively models the entire environment. We also propose a few strategies for their movement and study their effect in controlling the epidemic. Another application of this tool is provided in the domain of universal healthcare schemes. Universal healthcare means equality in access to medical facilities irrespective of any basis. With various countries having a different organizational structure and existing levels of medical facilities, this work models two of Indias well-known healthcare schemes and analyzes their performance differences. Developed as an application module over the same tool, the models can be optimized or customized to evaluate the schemes over various parameters. This analysis also provides an estimate of how successful the scheme is likely to be.
Applying deep learning in recognizing the femoral nerve block region on ultrasound images.

Background Identifying the nerve block region is important for the less experienced operators who are not skilled in ultrasound technology. Therefore, we constructed and shared a dataset of ultrasonic images to explore a method to identify the femoral nerve block region. Methods Ultrasound images of femoral nerve block were retrospectively collected and marked to establish the dataset. The U-net framework was used for training data and output segmentation of region of interest. The performance of the model was evaluated by Intersection over Union and accuracy. Then the predicted masks were highlighted on the original image to give an intuitive evaluation. Finally, cross validation was used for the whole data to test the robust of the results. Results We selected 562 ultrasound images as the whole dataset. The training set intersection over union (IoU) was 0.713, the development set IoU is 0.633 and the test set IoU is 0.638. For the single image, the median and upper/lower quartiles of IoU were 0.722 (0.647-0.789), 0.653 (0.586-0.703), 0.644 (0.555-0.735) for the training set, development set and test set respectively. The segmentation accuracy of the test set was 83.9%. For 10-fold cross validation, the median and quartiles of the 10-iteration sum IoUs was 0.656 (0.628-0.672); for accuracy, they were 88.4% (82.1-90.7%). Conclusions We provided a dataset and trained a model for femoral-nerve region segmentation with U-net, obtaining a satisfactory performance. This technique may have potential clinical application.
THEY KNOW: A PATHFINDING RATIONAL AGENT VIA KNOWLEDGE ACQUISITION MODELING FROM PLAYER BEHAVIOR AND ENHANCED A* ALGORITHM

Modern games have used Artificial Intelligence as a core element of game design and mechanics. Artificial Intelligence has thrived in many fields; however, the enhancement of pathfinding algorithms of AIs in games have remained stagnant. Moreover, numerous issues with regards to the exploitable plot of games have been raised by several gamers and game developers. The purpose of this research is to develop They Know - a survival themed thriller game with 4J MT-Adaptive A* - an adaptive and enhanced pathfinding algorithm created using A* as basis, to reduce the predictability of in-game agents by using the developed algorithm and by modifying agents with knowledge acquisition, to distinguish the personality and emotion of modern players based on the reaction of players to in-game situations, and to acquire data for determining the motivation of contemporary gamers for playing. The efficiency of the developed algorithm was compared with Lazy MT – Adaptive A* developed by Koenig (2007). Questionnaires developed by HEXACO, Power (2017), and Demetrovics (2011) were used as standards for acquiring data from the respondents to determine the respondents’ personality, degree of predictability of the game, and the motivation of players in playing. Data were gathered from grades 11 and 12 students of the University of Santo Tomas – Senior High School.
Engineering an enhanced thrombin-based GLP-1 analog with long-lasting glucose-lowering and efficient weight reduction

Peptides are considered as potent therapeutic drugs primarily due to the exquisite potency and selectivity to targets. However, the development and clinical application of peptide drugs were severely limited by the poor in vivo lifespans. Here, we designed an improved small albumin-binding polypeptide that can associate with human serum albumin (HSA) and liberate the bioactive peptide. Using glucagon-like peptide-1 (GLP-1) as a model, two new long-lasting GLP-1 analogs (termed XTS1 and XTS2) containing an albumin-binding domain, a protease-cleavable linker and a mutated GLP-1(A8Aib) were designed to demonstrate the sustained release of GLP-1 due to the plasma thrombin (TBN) digestion. Two XTS peptides were prepared of high purity (>99%) and accurate molecular weight determined by reversed high-performance liquid chromatography and mass spectrometry, respectively. In vitro measurements of surface plasmon resonance indicated that XTS1 associate with serum albumins of all species with higher affinity compared with XTS2. Metabolic stability of XTS1 in vitro in human plasma was also better than that of XTS2. Protease cleavage assay results of XTS peptides demonstrated the controlled-release of transient GLP-1 from the XTS1 and XTS2 mixture after thrombin-catalyzed hydrolysis. Then the intraperitoneal glucose tolerance test (IPGTT) showed that the glucose-lowering efficacies of XTS1 were in a dosage-dependent manner within the range of 0.1–0.9 mg kg−1. In addition, XTS1 showed similar hypoglycemic intensity and significantly longer action duration compared to Liraglutide in both multiple IPGTTs and hypoglycemic duration test. Apparently extended plasma half-lives of ∼2.3 and ∼3.5 days were observed after a single subcutaneous administration of XTS1 (0.9 mg kg−1) in rats and cynomolgus monkeys, respectively. Furthermore, twice-weekly subcutaneously dosed XTS1 in db/db mice achieved long-term beneficial effects on body weight, hemoglobin A1C (HbA1C) lowering and the function of pancreatic beta cells. These studies support that XTS1 exerts potential as a therapeutic drug for the treatment of T2DM.
TGM: A Generative Mechanism for Publishing Trajectories With Differential Privacy

We describe a new generative algorithm called trajectory generative mechanism (TGM) for publishing trajectory datasets with $\varepsilon $ -differential privacy guarantee, which achieves substantially higher computational efficiency and utility (practical) than the state-of-the-art algorithms. Our algorithm first encodes (models) the data as a graphical generative model and accurately captures the statistics of moving object trajectories. Using this model, TGM then privately generates synthetic trajectories such that the noise is optimally added to capture the movement direction of an object. Our algorithm preserves both the spatial and temporal information of trajectories in the generated dataset, requires less memory and computation than the competing approaches, and preserves the properties of real trajectory data in terms of traveled distance and stay location. We demonstrate the performance of TGM on both real and simulated datasets with a wide range of settings. Our experimental results show that TGM achieves high utility and efficiency by using the properties of the data.
Secure edge computing: An architectural approach and industrial use case

Internet of Things (IoT) perceived as the connection among heterogeneous thing or devices and end users anticipate for the rapid response or connection via their devices connected to the internet. This expectation of the users from the IoT, gave rise to many challenges (scalability, security, low end to end latency, etc.) and which motivated us to propose a novel architecture for the security of internet of smart edge computing. Edge computing is transforming the way of communication and proposed scheme will leverage it. The main trait of novel approach is the convergence of numerous technologies via exploiting communication between control gateways and sensor nodes/objects/things by intelligent computation and security. A use case from the industrial perspective implies its justification.
Blockchain-Based Mutual-Healing Group Key Distribution Scheme in Unmanned Aerial Vehicles Ad-Hoc Network

A dynamic group key is required for secure communication in the Unmanned Aerial Vehicles Ad-Hoc Network (UAANET). However, due to the unreliable wireless channel and high-dynamic topology of UAANET, the situation that a node is missing certain group key broadcast messages occurs frequently. Existing group key distribution schemes cannot be directly applied to the UAANET, because of their poor security or real-time. Therefore, we present a mutual-healing group key distribution scheme based on the blockchain. Firstly, the Ground Control Station (GCS) builds a private blockchain where the group keys distributed by GCS are recorded. Meanwhile, through the blockchain, a dynamic list of UAANET membership certificates is also managed. According to different attack models, a basic mutual-healing protocol and an enhanced one are designed based on the Longest-Lost-Chain mechanism to recover the node's lost group keys with the aid of its neighbors. Security analysis and extensive experiments show that, compared with the existing mutual-healing schemes, our proposed solution can effectively resist various attacks with small overhead on time and storage.
IP Protection and Supply Chain Security through Logic Obfuscation

The globalization of the semiconductor supply chain introduces ever-increasing security and privacy risks. Two major concerns are IP theft through reverse engineering and malicious modification of the design. The latter concern in part relies on successful reverse engineering of the design as well. IC camouflaging and logic locking are two of the techniques under research that can thwart reverse engineering by end-users or foundries. However, developing low overhead locking/camouflaging schemes that can resist the ever-evolving state-of-the-art attacks has been a challenge for several years. This article provides a comprehensive review of the state of the art with respect to locking/camouflaging techniques. We start by defining a systematic threat model for these techniques and discuss how various real-world scenarios relate to each threat model. We then discuss the evolution of generic algorithmic attacks under each threat model eventually leading to the strongest existing attacks. The article then systematizes defences and along the way discusses attacks that are more specific to certain kinds of locking/camouflaging. The article then concludes by discussing open problems and future directions.
At Home With Data: Family Engagements With Data Involved in Type 1 Diabetes Management

This article reports on an exploratory study of quantitative data use situated in families’ management routines while taking care of a child with Type 1 diabetes (T1D). T1D treatment requires frequent measurement and recording of numerical data about blood sugar concentration, nutritional intake, and insulin dosage at the child’s home, at school, and at other activities. We analyze coordination work between family members and others involved in the care of children with T1D using the lens of distributed cognition, and we introduce the notion of a data catchment to refer to the pathways of data flow and information storage within and between multiple agents and spaces. Interviews and observations reveal three main features of storage and use in data catchments: First, there is a great variability in how data move and are retained to enable communication between family members and others. Second, families tended to focus more on individual data points and less on aggregate readings despite some indications of ability to narrate through aggregate readings. Third, families engage in recurrent conversations and sometimes use novel artifacts to make numerical values meaningful to children with T1D. Implications for understanding this space of practice as constituting a data catchment are discussed.
Study on Membrane Separation and Its Physicochemical Properties of Theabrownin in ‘Zijuan’ Pu-erh Tea

3 500 Da decomposed dialysate and 100 000 Da undecomposed dialysate of the theabrownin in ‘zijuan’ pu-erh tea as the main content were obtained by using membrane technology and their physicochemical properties were studied.The result showed that the total acidic functional group,carboxyl group,phenolic hydroxyl group,tea polyphenols,polysaccharose content of 100 000 Da undecomposed dialysate were higher than those of 3 500 Da decomposed dialysate.The polysaccharide isolated from 100 000 Da undecomposed dialysate was composed of ribose,rhamnose,mannose,glucose and galactose,but these monose were not detected in 3 500 Da decomposed dialysate.It suggested that the 3 500 Da decomposed dialysate and 100 000 Da undecomposed dialysate contained the-OH and-COOH groups.It was suggested that the theabrownin of the ‘zijuan’ pu-erh tea belonged to benzene polyphenolic substance and contained of polyphenolic pigments,lipids,polysaccharide,protein and alkaloids.
Top-down Plantwide Control of a Parallel Double Effect Aqueous Lithium Bromide Absorption Chiller

An alternative control structure for a parallel double effect aqueous lithium bromide absorption chiller has been designed using top-down plantwide control structure analysis. Concept of self-optimizing control and location of throughput manipulator (TPM) have been utilized to improve performance of the control system economically. As the results, while a combination of liquid flowrate out of each generator is used as a self-optimizing measurement to control a spiting ratio, coefficient of performance (COP) can be increased up to 0.5% while heat source is supplied less than nominal value. In addition, by changing the position of TPM from chilled water flowrate to heat source flowrate, crystallization condition can be prevented more effectively, resulted in less back-off required and higher plant capacity by approximately 2.39%.
ALKALİ KATALİZATÖRLÜ ORGANİK DELİGNİFİKASYON SİSTEMLERİ

Geleneksel tam kimyasal kagit uretim proseslerinde, cevre ve insanlar uzerine zararli etkisi bulunan kukurtlu kimyasallar kullanmakta ve bu prosesler cok yuksek yatirim ve isletme maliyeti gerektirmektedir. Organik cozeltilerin tek baslarina veya diger solventlerle karisim halinde ve asitlerin katalizator olarak eklendigi alternatif kagit uretim prosesleri uzerine son zamanlarda yogun calismalar yapilmistir. Asitlerin katalizator olarak kullanildigi organik delignifikasyon reaksiyonlarinda, temel olarak ligninin polimerik yapisindaki alfa aril eter ve beta aril eter baglarinin asit hidrolizasyonu esastir. Bu calismada, dunya genelinde, geleneksel kimyasal metotlara alternatif olabilecegi labaratuvar duzeyindeki kanitlanmis ve kucuk olcekli tesis duzeyinde denemeleri yapilmis, Asam, Acetosolv, Formacell, Ester ve Milox organik delignifikasyon yontemleri incelenmistir. Bu yontemlerin her birisinin kendine ozgu proses ozellikleri bulunmaktadir. Fakat bu yontemlerin ortak ozelligi genel olarak geleneksel proseslerden daha basit ve bircok yonden avantajli sonuclar ortaya koymalaridir. Anahtar Kelimeler: Asit delignifikasyonu, Lignin, Kagit, Kagit hamuru, Asam, Acetosolv, Formacell, Ester, Milox.
High‐Precision, High‐Accuracy Oxygen Isotope Measurements of Zircon Reference Materials with the SHRIMP‐SI

Analytical protocols for SHRIMP‐SI oxygen isotope analysis (δ18O) of a suite of zircon reference materials (RMs) are presented. Data reduction involved a robust estimate of uncertainties associated with the individual spot as well as for groups where the spot data are combined. The repeatability of δ18O measurements is dependent on both the analytical conditions and the choice of the primary reference material. Under optimised conditions, repeatability was often better than 0.4‰ (2s) allowing sample uncertainties to be obtained to better than 0.2‰ (at 95% confidence limit). Single spot uncertainty combined the within‐spot precision with the scatter associated with repeated measurements of the primary zircon reference material during a measurement session. The uncertainty for individual spots measured under optimised conditions was between 0.3 and 0.4‰ (at 95% confidence). The analytical protocols described were used to assess a variety of zircon RMs that have been used for geochronology and for which laser fluorination oxygen isotope data are available (Temora 2, FC1, R33, QGNG and Plešovice), as well as zircons that have been used as RMs for trace element or other types of determination (Mud Tank, Monastery, 91500, AS57, AS3, KIM‐5, OG1, SL13, CZ3 and several other Sri Lankan zircons). Repeated analyses over nine sessions and seven different mounts show agreement within analytical uncertainty for Temora 2, FC1, R33, QGNG, Plešovice and 91500, when normalised to Mud Tank. For existing ion microprobe mounts with these materials, an appropriate δ18O can be determined. However, care should be taken when using zircons from the Duluth Complex (i.e., FC1, AS57 and AS3) as reference materials as our data indicated an excess scatter on δ18O values associated with low‐U zircon grains.