Miracle-dz/UniFAR-FTUs huggingface dataset:
New Spectrophotometric Estimation and Cloud Point Extraction of Cefdinir

A sensitive spectrophotometric method was developed for the estimation of cefdinir (CFD), a cephalosporin species. This study involves two methods, and the first method includes the preparing of azo dye by the reaction of CFD diazonium salt with 4-Tert-Butylphenol (4-TBP) and 2-Naphthol (2-NPT) in alkaline medium, which shows colored dyes measured at λmax 490 and 535 nm, respectively. Beer's law was obeyed along the concentration range of (3-100) μg. ml -1 . The limits of detection were 0.246, 0.447 μg. ml -1 and molar absorptivities were 0.6129×10, 0.3361×10 L.molcm for (CFD-4-TBP) and (CFD-2-NPT), respectively. The second method includes preconcentration for cefdinir dyes by using cloud point extraction in the presence of Triton X-114 (10% v/v) and recording measurements using the UV-Visible technique. Cloud point extraction enables the drug to be precisely estimated under the optimal experimental conditions. The concentrations were ranged between (0.1-6.0) and (0.2-6.0) μg. ml -1 . The limits of detection were 0.032, 0.054 μg. ml -1 and molar absorptivities were 0.4733×10, 0.2788×10 L.molcm, respectively. Enrichment factors were 24.61, 24.58, and distribution coefficients were 1526, 1393 for (CFD-4-TBP), (CFD-2-NPT), respectively. The proposed methods have been applied for the determination of CFD in commercial formulation with no interference. The results appear to be no significant difference between the two methods.
“CARE” in social media: perceptions of reputation in the healthcare sector

Guided by the growing importance of social-mediated organisational communication, this study examines how communication professionals within healthcare organisations perceive and respond to the reputation impacts of social media on the organisation’s reputation. Although the healthcare sector finds itself in the midst of a (continually) transforming landscape characterised by large amounts of digital health (mis)information and an empowered “patient-as-consumer”, little is known about how professionals in this sector understand the changes and respond to them. Moreover, much extant scholarship on the topic is published in specialised health or medical journals and does not explicitly address the communication implications for healthcare organisations. ,In-depth semi-structured interviews were conducted with communication professionals responsible for social media across eight hospitals in the Netherlands. The sample included two participants working as communication consultants/social media advisors for healthcare organisations. In all, 15 interviews were conducted. ,Building on interviewee perspectives, the authors advance the CARE (Control, Access(ability), Responsive(ness) and Engagement) model of social-mediated communication, highlighting the dualistic characteristics of each dimension. This model is built upon a careful analysis of healthcare professional responses. In an always-on environment, understanding and managing the tensions within the authors’ model may be decisive to the reputation implications of social media use. ,Understanding the tensions within each dimension lends a more nuanced perspective on the potential impact(s) of social media as experienced by professionals in the field. In shifting away from a binary, either/or approach, the paper contributes to explicating the complexities of a pervasive phenomenon (i.e. social-mediated communication) and its multifaceted impacts on the healthcare sector.
Investigations Into the Mobilization of Actinides From ILW Conditioned in Cement and Bitumen and Studies of their Sorptive and Migration Behaviour in Both the Near- and Far-Fields for a Repository Contained in a Deep Salt Environment

Experiments have been carried out into the leaching of ILW conditioned in cement and bitumen in concentrated salt solutions. Although difficult to observe with real waste leachates, investigations into the leaching of a simulated waste in cement have indicated leached transuranic levels of ca 10/sup -9/ M; the amount of activity leached by a quinary salt solution being 10/sup 2/ - 10/sup 3/ times higher. this has been interpreted in terms of a pH effect. For the real waste, alpha-spectroscopy has indicated a significantly larger release of Cs from cement than from bitumen. For all waste samples a notable absence of colloidal material was observed; an observation which can be explained in terms of the high solution ionic strengths and the corresponding influence upon radionuclide solvation. Transuranic mobility studies through salt and sand from a salt dome in Northern Germany have shown the presence of at least two types of species of wildly differing mobility; one migrating with approximately the same velocity as that of the solvent front and the other strongly retarded. Actinide recoveries (i.e. that passing through the columns) could be strongly influenced by either changing the system pH or by the addition of a competitor such asmore » Ce; the latter effect pointing to a competitive sorption. « less
Integrating E-Learning Technologies in Business Education Course Delivery During Covid-19 Lockdown in South-South Nigeria

This study investigates the acceptability of utilizing e-learning technologies for business education course-delivery during the period of tertiary institutions lockdown as a result of COVID-19 pandemic in south-south, Nigeria. Hinged on the theory of Technology Acceptance by Davis, F. D, a descriptive survey research design using quantitative and qualitative approach was adopted. Data was collected via questionnaire, and Focus Group Discussion (FGD) was used for the qualitative approach. The study revealed that business educators utilized elearning technologies to a very low extent during the pandemic. Therefore, strategies to forestall such hindrances and difficulties were identified and discussed.
The Proximal Bootstrap for Constrained Estimators

We demonstrate how to use the proximal bootstrap to conduct asymptotically valid inference for ? n -consistent estimators deﬁned as the solution to a constrained optimization problem with a possibly nonsmooth and nonconvex sample objective function and a constraint set deﬁned by smooth equalities and/or inequalities that can be either non-random or estimated from the data at the ? n rate. The proximal bootstrap estimator is typically much faster to compute than the standard bootstrap because it can be written as the solution to a quadratic programming problem. Monte Carlo simulations illustrate the correct coverage of the proximal bootstrap in a boundary constrained nonsmooth GMM model, a conditional logit model with estimated capacity constraints, and a mathematical programming with equilibrium constraints (MPEC) formulation of the Rust (1987) Bus Engine Replacement model proposed in Su and Judd (2012).
INFLUENCE OF THE PRODUCTION PARAMETERS ON THE TRANSVERSAL PERMEABILITY OF PREFORMS PRODUCED WITH AUTOMATED FIBRE PLACEMENT

Automated Fibre Placement has been established for serial production of complex CFRP parts within the last years. While most applications are using conventional prepreg and autoclave production chains the potential of dry bindered materials is turning into focus. Following the preforming process, usually one of the numerous liquid composite moulding technologies with transversal impregnation direction is used. A challenge still is the reproducible and reliable impregnation of the compact and undulation free preforms. The dominating parameter for this process is the transversal permeability. Within the presented work, several production parameters of the AFP production process such as the compaction force and binder activation temperature have been investigated and their influence on the transversal permeability was tested. Moreover, the effect of the distribution of gaps within the preform, known as staggering, was analysed.
Design and Prototyping of a Transformable Quadruped Robot An Undergraduate Honors Thesis Presented to The Department of Mechanical Engineering The Ohio State University In Partial Fulfillment of the Requirements for Graduation with Distinction in Mechanical Engineering by

ii Acknowledgement . iii List of Figures . vi List of Tables . vii Chapter 1: Introduction of the thesis . 1 1.1 Legged Robots . 1 1.2 Quadruped Robots . 1 1.3 Wheeled Robots . 4 1.4 Transformation mechanism. 4 1.5 Objectives of this research . 5 1.6 Overview of the thesis . 5 Chapter 2: Design Specifications . 6 2.1 Constraints . 6 Chapter 3: Conceptual Design . 7 3.1 Dimensioned design of the robot . 7 3.2 Kinematics analysis . 8 3.3 Approaches of the concepts of the transformation mechanism / actuators selection . 12 3.4 D printing study . 15 Chapter 4: Design of the transformable quadruped robot . 17 4.1 Design of the forearm . 17 4.2 Design of the main arm . 18 4.3 Design of the shoulder . 20 4.4 Design of the transformation process . 21 4.5 Simulation of designed parts and assemblies . 22 4.6 Trajectory generation . 25 Chapter 5: Testing procedures and results . 29 5.1 Goal of testing . 29 5.2 Testing setup . 29 5.3 The testing procedure . 32 v 5.4 Testing results . 32 5.5 Discussion of the leg motion testing . 35 Chapter 6: Conclusions of the thesis . 37 6.1 Contributions. 37 6.2 Future work . 38 6.2.1 Mechanical design: . 38 6.2. 2 Testing: . 39 6.3 Summary of the thesis . 39 Reference . 41
Application of Nanotechnology in Food Technology- A review Paper

Ongoing advancements in nanotechnology have changed a few logical and modern regions including the food business. Utilizations of nanotechnology have arisen with the expanding need for nanoparticle utilizes in different fields of food science and food microbiology, including food preparing, food bundling, utilitarian food advancement, sanitation, identification of foodborne microorganisms, and timeframe of realistic usability augmentation of food as well as food items. This audit sums up the capability of nanoparticles for their utilizations in the food business to give purchasers a safe and tainting free food and to guarantee the customer agreeableness of the food with improved utilitarian properties. Parts of the use of nanotechnology about expansions in food sustenance and organoleptic properties of food sources have likewise been examined momentarily alongside a couple of experiences on security issues and administrative worries on nano-prepared food items.
Part II. Application to the land carbon cycle in the MPI Earth System Model

The Response Function Identification method introduced in the first part of this study is applied here to investigate the land carbon cycle in the Max Planck Institute for Meteorology Earth System Model. We identify from standard CMIP 1% experiments the linear response functions that generalize the land carbon sensitivities β and γ. The identification of these generalized sensitivities is shown to be robust by demonstrating their predictive power when applied to experiments not used for their identification. The linear regime for which the generalized framework is valid is estimated, and approaches to improve 5 the quality of the results are proposed. For the generalized γ-sensitivity, the response is found to be linear for temperature perturbations until at least 6 K. When this sensitivity is identified from a 2×CO2 experiment instead of the 1% experiment, its predictive power improves, indicating an enhancement in the quality of the identification. For the generalized β-sensitivity, the linear regime is found to extend up to CO2 perturbations of 100 ppm. We find that nonlinearities in the β-response arise mainly from the nonlinear relationship between Net Primary Production and CO2. By taking instead of CO2 the resulting Net Primary 10 Production as forcing, the response is approximately linear until CO2 perturbations of about 850 ppm. Taking Net Primary Production as forcing also substantially improves the spectral resolution of the generalized β-sensitivity. For the best recovery of this sensitivity, we find a spectrum of internal time scales with two peaks, at 4 and 100 years. Robustness of this result is demonstrated by two independent tests. We find that the two-peak spectrum can be explained by the different characteristic time scales of functionally different elements of the land carbon cycle. The peak at 4 years results from the collective response 15 of carbon pools whose dynamics is governed by fast processes, namely pools representing living vegetation tissues (leaves, fine roots, sugars, and starches) and associated litter. The peak at 100 years results from the collective response of pools whose dynamics is determined by slow processes, namely the pools that represent the wood in stem and coarse roots, the associated litter, and the soil carbon (humus). Analysis of the response functions that characterize these two groups of pools shows that the pools with fast dynamics dominate the land carbon response only for times below 2 years. For times above 25 years the 20 response is completely determined by the pools with slow dynamics. From 100 years onwards only the humus pool contributes to the land carbon response. 1 Identification of linear response functions from arbitrary perturbation experiments in the presence of noise – https://doi.org/10.5194/npg-2021-10 Preprint. Discussion started: 19 March 2021 c © Author(s) 2021. CC BY 4.0 License.
Network Service Embedding for Cross-Service Communication

Network Function Virtualization (NFV) facilitates the deployment and orchestration of network services (NSes) on virtualized infrastructures. NFV orchestration, in its prevailing form, deals with NSes independent to each other. This introduces significant limitations to cross-service interactions, i.e., a service that requires the consumption of (part of) another service. In an evolving service ecosystem that promotes cross-service interactions, orchestrating NSes with their cross-service communication (CSC) requirements into account is of crucial importance. In this paper, we propose a CSC-aware NS embedding heuristic that optimizes NS placement, not only based on inner-component resource and communication demands, but also with respect to another deployed NS that will be consumed. To this end, we study potential types of CSC and introduce a new data structure, namely VNF embedding tree, which is used to generate the most appropriate embedding sequence. Assessing the efficiency of the proposed heuristic using simulations, we uncover significant gains in terms of service co-location without any perceptible embedding efficiency penalty, compared to a baseline heuristic that is oblivious of CSC.
C2QoS: CPU-Cycle based Network QoS Strategy in vSwitch of Public Cloud

The network Quality-of-Service (QoS) strategy in vSwitch aims to guarantee the Service-Level-Agreement (SLA) for the concurrent Virtual Machines (VMs) residing on a particular server platform. Different from a hardware switch, the traffic forwarding tasks in vSwitch are completed by processes/threads running on some dedicated CPU cores. Existing vSwitch QoS strategies, inherited from the solutions in the hardware switch, are interface-based and ignore the isolation of these IO-dedicated CPU resources among VMs. As the result, they cannot ensure VMs’ SLA targets due to the resource contention. In order to resolve the issue, we propose a CPU-Cycle based QoS (C2QoS) strategy, that contains a CPU-Cycle based Token-Bucket (C2TB) mechanism and a Hierarchical Batch Scheduling (HBS) mechanism. The C2TB apportions the IO-dedicated CPU resources to each VM for ensuring bandwidth, while the HBS schedules the VMs’ forwarding tasks on these CPU cores to guarantee hierarchical latency. We implement the C2QoS strategy on the Data Plane Development Kit accelerated Open vSwitch (OVS-DPDK) platform. Experimental results show that compared with existing strategies, the influence of CPU resource congestion on bandwidth is eliminated and that on latency is reduced by 80%.
Exploiting Uncertainty in Triangulation Light Curtains for Object Tracking and Depth Estimation

Active sensing through the use of Adaptive Depth Sensors is a nascent ﬁeld, with potential in areas such as Advanced driver-assistance systems (ADAS). One such class of sensor is the Triangulation Light Curtain, which was developed in the Illumination and Imaging (ILIM) Lab at CMU. This sensor (comprising of a rolling shutter NIR camera and a galvom-irror with a laser) uses a unique imaging strategy that relies on the user providing the depth to be sampled, with the sensor returning the return intensity at said location. Prior work demonstrated eﬀective strategies for local depth estimation, but failed to take into account the physical limitations of the galvomirror, work over long ranges, or exploit the triangulation uncertainty in the sensor. Our goal is this thesis is to demonstrate the eﬀectiveness of this sensor in the ADAS space. We do this by developing planning, control and sensor fusion algorithms that consider the device constraints, and exploit the device’s physical eﬀects. We present those results in this thesis. I would like to thank my advisor Srinivas, and various CMU folks including Joe Bartels,
Message-Aware Cryptographic Primitives

We introduce a new type of cryptographic primitives which enforce high communication or storage complexity. We call such cryptographic primitives “message aware”. Intuitively, a function is message-aware if to evaluate it on a random input one has to engage in a protocol of high communication complexity, or one has to use a lot of storage. Therefore, the ability to compute such function constitutes certain “proof of work”, because the computing party is forced to contribute a lot of its communication or storage resources to this task. Such primitives can be used in applications which deal with non-malicious but sellﬁshly resource-maximizing parties. For example, they can be useful in constructing peer-to-peer systems which are robust against so called “free riders”. In this paper we deﬁne two such primitives, a message-aware signature and a message-aware commitment scheme, and we give heuristic constructions for both.
Loss of Function of OsARG Resulted in Pepper-Shaped Husk in Indica Rice

Grain shape is one of the most important and complex traits determining the grain yield in rice. In this study, we discovered two rice mutants with defective shape spikelets, designated as psh1-1/2 (pepper-shaped husk 1-1/2), which were both isolated from the tissue-culture-regenerated plants of indica cultivar Minghui 86. The two mutants showed the same mutant phenotypes, containing pepper-shaped spikelets; shorter, smaller and compact panicles; very low seed-setting rate; high percentage of split grains; and lower grain width. Genetic analysis indicated that the mutant phenotypes were controlled by a recessive gene. Gene mapping indicated that the target gene PSH1 was located on the short arm of chromosome 4. Sequencing analysis revealed that the two mutants each had a different nonsense mutation in OsARG, confirming that the target gene is OsARG. Compared with the previously reported OsARG mutant nglf-1, psh1-1/2 possessed some distinct mutant phenotypes, probably because of the influence of different genetic background, suggesting that OsARG may function differently under different genetic backgrounds.
Exploring the Limits of Word Sense Disambiguation for Russian using Automatically Labelled Collections

There is a long-standing problem in the field of the word sense disambiguation (WSD) that is known as the knowledge acquisition bottleneck. Many state-of-the-art WSD algorithms are data-hungry, so the lack of the sense-annotated data hinders the development of supervised WSD models for the low-resource languages such as Russian. In this work we introduce an algorithm of automatic generation and labelling of the training collections based on the monosemous relatives concept. This method relies on the RuWordNet thesaurus and the relations between ambiguous words and the monosemous words they are connected to. Our approach addresses the issues of the limited availability of the examples for some polysemous word senses and the bias that can be possibly introduced by some training samples. The experiments attested that the generated collections enable a wide coverage of the polysemous words presented in RuWordNet, and the models trained on these collections can attain a good overall performance on the Russian WSD benchmarks.
A survey paper on bias corrected fuzzy based image clustering in brain MRI

ABSTRACT Magnetic resonance Image (MRI) is a medical image method use in radiology to visualize internal body structures like tissues. MRI method provides high-quality contrast effect to visual tissues of brain and MRI contrast is enhancing appearance of tumors in brain. In this survey compared the CLIC, EM, AFCM, Bias Field Estimation, SFKFCM, MFCM and FLGMM methods for accurate brain segmentation in MRI images. CLIC method to evaluate metric tissue classification and estimate bias field minimizing energy, optimal bias field derived smoothness of CLIC method. It’s applied for fully automated applications. AFCM applied on corrupted images in reality accurate in classification and partial volume effect. MR data corrupted truth brightness variation in each component. AFCM implementation is faster than other methods one major problem in AFCM method is to look for clusters of the same shape, size and increased complexity. Bias corrected FCM method with spatial neighborhood regularization period and its time taking; lacks robustness to noise is main problem of the method. In GKFCM method with a spatial bias correlation can automatically learn parameters by prototype driven learning scheme and this method is effective more robust to noise. SFKFCM method for segmenting brain MRI images and correcting spurious variations, to improve the separability of observed data, fast clustering scheme improve speed up process and execution time is reduced improved clustering results. MFCM for adaptive segmentation and intensity correlation of MR images and automation available for the segmentation of MR images into tissues classes correcting interscan intensity inhomogenetics. MFCM leads to increased improvement in quality of 3D brain structures and visualization. GMM voxel intensities in each target region, its lack of taking spatial information and uncertainty data may produce poor segmentation result. To overcome problem in segmentation FGMM concept is proposed for uncertainty data and parameter quality improvement. The integration of the weighted GMM energy functions in the entire image and uses a truncated Gaussian kernel function to incorporate spatial constraints into local GMM employ the fuzzy membership function to balance each GMM segmentation process. FGMM reduced noise, low contrast, bias field and improved segmentation result compared with all other methods proposed by previous researches.
Learn to Play Tetris with Deep Reinforcement Learning

Tetris is one of the most popular video games ever created, perhaps in part because its difﬁculty makes it addictive. In this course project, we successfully trained a DQN agent in a simpliﬁed Tetris environment with state-action pruning. This simple agent is able to deal with the Tetris Problem with reasonable performance. We also applied several state of the art reinforcement learning algorithms such as Dreamer, DrQ, and Plan2Explore in the real-world Tetris game environment. We augment the Dreamer algorithm with imitation learning as Lucid Dreamer algorithm. Our experiments demonstrate that the mentioned state of art methods and their variants fail to play the original Tetris game. The complex state-action space make original Tetris a quite difﬁcult game for non-population based reinforcement learning agents. (Video link).