Miracle-dz/UniFAR-FTUs huggingface dataset:
Laboratory Calibration of TDR Probes for Simultaneous of Measurements Soil Water Content and Electrical Conductivity

ABSTRACT Accurate measurement of water content (θ), apparent electrical conductivity (ECa) of soils, and soil solution electrical conductivity (ECw) is critical for a better management of irrigation water and the effective monitoring and control of soil salinity. In this paper, we demonstrate the design and validation of an identical time domain reflectometry (TDRWO) probe for accurate and non-destructive measurements of ECw. Two calibration functions were used to determine the soil-water content by TDR. Theses relations were verified by laboratory experiment over a wide range of θ and bulk density (BD) for dune sand. The exact length and the impedance of all TDR-probes were calibrated using the WinTDR procedure. Estimates of ECw were based on θ and the bulk ECa using a special modeling approach which applies long-time TDR waveform analysis. The geometrical disposition of the matrix phase factors (τ and β) was calculated by immersing the TDR probe in sodium chloride (NaCl) solutions of different electrical conductivities in pressure cells wetted and drained with each of these NaCl solutions. The reliability of the TDRWO was validated/proven under laboratory conditions. The laboratory experiment consisted in inserting the TDR probe into a pressure cell packed with mixed sand and 2-mm sieved loam soil that was subsequently wetted and drained with different NaCl solutions at various pressure heads. The ECw estimated by TDRWO was compared to the ECw measured in the draining solutions after they stabilized in the soil porous system. The τ and β factors calculated for the ceramic disks sets were 1.991 and 4.312, respectively. In the laboratory experiments, high and therefore significant correlations (R2 = 0.986; P < .001) were found between the ECw estimated by the TDRWO and the corresponding ECw values measured in the column-drainage. These results demonstrate that the TDRWO is an instrument which allows researchers to accurately estimate soil solution salinity independently of the soil water content and the porous medium in which the TDR probe is installed. Test results showed that the TDR method has high accuracy for monitoring soil water content but is less accurate in monitoring soil electrical conductivity across a water content range of about ≤0.03cm3/cm3. Regression analysis between TDR-Volumetric water content (ϴv) and weighing method – ϴv showed good correlation with an R2 of 0.97 and 0.98 during two laboratory experiments.
A Method to Establish a Trade-Space of System Requirements and Life Cycle Cost

Systems engineering traditionally approaches the design of systems through determination of requirements for and implementation of a system. The system is conceived as something to enable achievement of an effect with the tacit assumption that the system to be designed must achieve technical performance, including availability characteristics, which enable delivery of the whole of the intended effect. This approach determines the technical requirements of the system to ensure achievement of the system purpose under assumptions about how the system, or fleet, would be deployed to provide the intended service. Usually, cost is addressed after requirements, either to find the cheapest method to achieve the requirements or as one dimension of a trade-space analysis. In this paper, we explore a different philosophy for finding the system requirements; starting with the required system level service provision, but agnostic about the technical quality needed. We investigate a trade-space including the life cycle cost (LCC) of service provision as a contribution to determining subsystem requirements. We model the life cycle, for many variations of technical composition, using a Monte Carlo method, and show that a trade-space of LCC and requirements is likely to produce a cheaper solution than starting with sub-system requirements.
A histological and immunohistochemical study on testicular changes induced by sliver nanoparticles in adult albino rats and the possible protective role of camel milk.

Introduction: Silver nanoparticles (AgNPs) are broadly used in medicine and food industry, associated with potential toxicity in many organs. Camel milk (CM) is an excellent source of human nutrition and has many health benefits in prevention of diseases. Aim of the work: To assess the effect of two different doses of AgNPs on the testis of adult rats and the possible protective role of CM. Material and methods: Forty-five adult male rats were divided into five groups, Group I: control rats, Group II: rats treated with low dose of silver nanoparticles, Group III: rats treated with high dose of AgNPs, Group IV: rats treated with low dose of AgNPs and camel milk, Group V: rats treated with high dose of AgNPs and camel milk. Testicular specimens were processed, then examined histologically and immunohistochemically. Testosterone hormonal assay were done. Morphometrical studies and statistical analysis were conducted.Results: Group II showed mild harmful effect, while Group III had severe damaging changes on the seminiferous tubules. They showed a significant increase (P < 0.01) of α-SMA, a significant decrease(P
Engaging Learning Models with Information and Communication Technologies in Advancing Electronic Learning

Emerging information and communication technologies and learning models have triggered a new wave of educational innovation: electronic learning (E-learning). This study employs a hypercube innovation model to analyze the differences in technology and learning models in conventional (face-to-face) classroom learning and E-learning environments. The results of the analyses indicate that the innovation from traditional classroom learning to E-learning is radical for both the learner and instructor, leading to drastic changes in the technology and learning model. For education institutions, the technology is a fundamental change, while the learning model is reinforced. From the dynamic capability perspectives, a set of core capabilities needed for successfully exploiting E-learning is identified. These results provide insight for learners, instructors, and education institutions for enhancing their understanding of E-learning innovation and provide guidelines to help E-learning stakeholders adapt from conventional classrooms to E-learning environments. DOI: 10.4018/978-1-61520-623-0.ch015
Networked Filtering and Fusion in Wireless Sensor Networks

By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. Networked Filtering and Fusion in Wireless Sensor Networks introduces the subject of multi-sensor fusion as the method of choice for implementing distributed systems.The book examines the state of the art in information fusion. It presents the known methods, algorithms, architectures, and models of information fusion and discusses their applicability in the context of wireless sensor networks (WSNs). Paying particular attention to the wide range of topics that have been covered in recent literature, the text presents the results of a number of typical case studies.Complete with research supported elements and comprehensive references, this teaching-oriented volume uses standard scientific terminology, conventions, and notations throughout. It applies recently developed convex optimization theory and highly efficient algorithms in estimation fusion to open up discussion and provide researchers with an ideal starting point for further research on distributed estimation and fusion for WSNs.The book supplies a cohesive overview of the key results of theory and applications of information-fusion-related problems in networked systems in a unified framework. Providing advanced mathematical treatment of fundamental problems with information fusion, it will help you broaden your understanding of prospective applications and how to address such problems in practice.After reading the book, you will gain the understanding required to model parts of dynamic systems and use those models to develop distributed fusion control algorithms that are based on feedback control theory.
Adaptive Fault Detection Technology Research Based on Distributed Database Disaster

Distributed storage systems demonstrate superior performance in terms of capacity, I/O throughput and scalability, but the reliability of inexpensive components is not high, and it is easy to cause catastrophic consequences of data loss. Fault detection is a key technology to provide high availability for distributed system, the new adaptive fault detection system architecture is proposed in this paper, which considered availability and disaster recovery ability, is divided into four levels: 1) Client layer: in this layer, customers can keep in touch with local network or outside network disaster recovery/backup center; 2) Server layer: in this layer, the high availability is guaranteed by its backup scheme; 3) Local recovery layer: in this layer, data backup and recovery are realized through local real-time replication; 4)Remote recovery layer: in this layer, data backup and recovery are realized (delayed) through remote backup database. And we evaluated and tested this method in our lab network environment.
MayaVi: A free tool for CFD data visualization

Visualizing CFD data is extremely important. There are very few freely available tools that allow one to visualize scalar and vector data on rectilinear, structured and unstructured grids. MayaVi is a free tool developed by the author that helps visualize such CFD data. It uses the Visualization Toolkit (VTK) for the actual visualization and provides a useful graphical user interface to make visualizing the data easy. This article describes the tool and the basis for its development.
Postnatal Effect Of Acrylamide On Rat Renal Cortex And The Protective Effect Of Ginger (Zingiber Officinale Roscoe)

Background: Acrylamide is toxic both in experimental animals and in humans. It is proved to be carcinogenic in rodents and considered by The International Agency for Research on Cancer as a probable human carcinogen. Medicinal plants have significant antioxidant properties. Ginger had the highest antioxidant activity among these plants.Aim of the work: To detect the histopathological effects of acrylamide on the kidneys in postnatal rats and to determine the possible protective effect of Ginger (Zingiber officinale Roscoe) as an antioxidant.Methods: The experimental pregnant rats were randomly divided into 3 groups:Group 1 (control group): these rats were preserved under normal condition of diet and water. Group 2 (acrylamide-treated group): acrylamide was orally administered to non-anesthetized rats by gastric intubation at a dose of 10 mg/kg/day. Group 3 (ginger-protected group): animals of this group were given the same dose of acrylamide as in group 2 followed by 1 ml of final aqueous extract of ginger (24 mg/ml) three times weekly. All the doses were administered from the 7th day of gestation and continued up to 21 days after delivery. Postnatal rats at the 2nd and 21st days were selected from each group and were scarified. Their kidneys were carefully dissected, removed and fixed in 10% formalin for histopathological and immunohistochemical examinations.Results: Maternal acrylamide administration disturbed the development of the renal cortex of the offsprings. Histological examination of acrylamide-treated, 2-day-old rats revealed degenerated glomeruli with lack of capillary tufts, disarrangement of podocytes and thickening of the parietal layers of Bowman's capsules. Moreover, the damage was evident in the primitive tubules. Examination of acrylamide-treated, 21-day-old rats showed congested glomerular capillaries, mesangial hypercellularity, vacuolations and darkly stained nuclei of the renal tubular epithelium, and extensive interstitial cellular infiltration and hemorrhage. Statistically, acrylamide–treated groups at both ages showed a highly significant decrease in the mean glomerular count, and the mean thickness of the cortex and the medulla as compared to their control groups. Moreover, the area percentage of renal NF-kβ protein expression showed a significant increase with acrylamide treatment. Ginger administration effectively restored most of the acrylamide-induced renal cortical damage.Conclusion: ginger administration effectively restored most of the acrylamide-induced renal cortical damage, suggesting that ginger supplement can play a protective role against acrylamide deleterious effects.
Estimation of Graphical Models with Biological Applications

Yuying Xie: ESTIMATION OF GRAPHICAL MODELS WITH BIOLOGICAL APPLICATIONS (Under the direction of Yufeng Liu and William Valdar) Graphical models are widely used to represent the dependency relationship among random variables. In this dissertation, we have developed three statistical methodologies for estimating graphical models using high dimensional genomic data. In the first two, we estimate undirected Gaussian graphical models (GGMs) which capture the conditional dependence among variables, and in the third, we describe a novel method to estimate a Gaussian Directed Acyclic Graph (DAG). In the first project, we focus on estimating GGMs from a group of dependent data. A motivating example is that of modeling gene expression collected on multiple tissues from the same individual. Existing methods that assume independence among graphs are not applicable in this setting. To estimate multiple dependent graphs, we decompose the problem into two graphical layers: the systemic layer, which is the network affecting all outcomes and therefore describing cross-graph dependency, and the category-specific layer, which represents the graph-specific variation. We propose a new graphical EM technique that estimates the two layers jointly; and also establish the estimation consistency and selection sparsistency of the proposed estimator. We confirm by simulation and real data analysis that our EM method is superior to a naive one-step method Next, we consider estimating GGMs from noisy data. A notable drawback of existing methods for estimating GGMs is that they ignore the existence of measurement error which is common in biological data. We propose a new experimental design using technical replicates, and develop a new methodology using an EM algorithm to efficiently estimate the sparse GGM by taking account the measurement error. We systematically study the asymptotic properties of the proposed method in high dimensional settings. Simulation iii study suggests that our method have substantially higher sensitivity and specificity to estimate the underlying graph than existing methods. Lastly, we consider the estimation of the skeleton of a Directed Acyclic Graph (DAG) using observational data. We propose a novel method named AdaPC to efficiently estimate the skeleton of a DAG by a two-step approach. The performance of our method is systematically evaluated by numerical examples.
A bidirectional trace simplification approach based on a context switch linked list for concurrent programs

Concurrent programs are notoriously difficult to debug due to shared memory and the non‐determined nature of thread scheduling. Frequent context switches add a huge burden on developers in reasoning about concurrency bugs. To alleviate this problem, we present a bidirectional trace simplification approach based on a context switch linked list. First, we calculate the dependence relations, including local dependences, synchronization dependences, and remote read/write dependences. Second, we construct a context switch linked list according to the original buggy trace. Then, we backward refactor the context switch linked list in sequence to extend thread execution intervals. Finally, we forward check the context switch linked list in sequence to ensure that no nodes can be further merged. We have conducted experiments on eight Java multi‐threaded programs to evaluate our approach. The results show that our approach performs better than or is comparable to the compared static approaches in effectiveness and efficiency.
VAS-AKA: An Efficient Batch Verification Protocol for Value Added Services

In this paper, we introduce an efficient batch oriented authentication and key agreement protocol for value added services named VAS-AKA to authenticate multiple requests sent from different mobile stations at a time. The reliability of the protocol is discussed along with the algorithm to detect one or more invalid mobile user(s) in a batch. The security analysis and performance evaluation in terms of communication and computation overhead, batch and re-batch verification delay is presented. Using this protocol, the authentication server efficiently able to verify authentication requests sent from multiple mobile users. Index Terms—Authentication, batch verification, security, VAS
Fault Tolerance Techniques in Big Data Tools:A Survey

Big Data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process the data within a tolerable elapsed time. Fault tolerant system is one that can provide continue correct performance of its specified tasks in presence of failure.This paper is based on a survey of different kind of fault tolerance techniques in big data tools such as Hadoop and MongoDB.
Path-Goal Theory and the Application in Educational Management and Leadership

This study focuses on Path-Goal theory and application in educational management and leadership, which is categorized under contingency approach of leadership. The theory proposed that the behaviour of leaders' can be exercised through different approaches, times, and situations by the same leader. The purpose of this paper is to highlight path-goal leadership theory. An important aspect of this paper hinges on the application of path-goal theory in an educational institution using leadership approaches in terms of supportive, directive, achievement-oriented, and participative behaviour on subordinate in achieving task completion. It is concluded that education leaders should put in use the path-goal leadership approaches in their daily dealings with their subordinate in their various educational institution. <br><br>
Self-Assembly of Two-Dimensional Colloids in Spherical Space

Understanding the hierarchical organization of nanomaterials in different geometries is important for developing materials with new properties. It is well known that long-range ordering emerges when shape-anisotropic nanoparticles form liquid crystals; this may offer an opportunity to build large-scale ordered structures assembled by nanoparticles in a confined geometry. This study demonstrates the self-assembly of two-dimensional colloids of graphene oxide (GO) in a spherical space. The arrangements of GO nanosheets were captured by in situ photopolymerization to form microspheres, in which the nanosheets organized into lamellar liquid crystalline structures, adopting either a concentric configuration or a pseudo-concentric configuration, leaving topological defects in the central region. We also observed GO microspheres with bipolar-like configurations although they are scarce. Optical and electron microscopy observations revealed the fine structures of these topological defects caused by the frustratio.
Rapid and efficient in vivo angiogenesis directed by electro-assisted bioprinting of alginate/collagen microspheres with human umbilical vein endothelial cell coating layer

Abstract Rapid reconstruction of functional microvasculature is the urgent challenge of regenerative medicine and ischemia therapy development. The purpose of this study was to provide an alternative solution for obtaining functional blood vessel networks in vivo, through assessing whether hydrogel-based microspheres coated by human umbilical vein endothelial cells (HUVECs) can direct rapid and efficient in vivo angiogenesis without the addition of exogenous growth factors or other supporting cells. Uniform alginate microspheres with adjustable diameter were biofabricated by electro-assisted bioprinting technology. Collagen fibrils were evenly coated on the surface of alginate microspheres through simple self-assembly procedure, and collagen concentration is optimized to achieve the highest HUVECs adhesion and proliferation. Immunofluorescence staining and gene analysis confirmed the formation of the prevascularized tubular structure and significantly enhanced endothelial gene expression. HUVECs-coated hydrogel microspheres with different diameters were subcutaneously injected in immune-deficient mice, which demonstrated rapid blood vessel regeneration and functional anastomosis with host blood vessels within 1 week. Besides, microsphere diameter demonstrated influence on blood vessel density with statistical differences but showed no obvious influence on the area occupied by blood vessels. This study provided a powerful tool for rapid and minimal-invasion angiogenesis of bioprinting constructs and a potential method for vascularized tissue regeneration and ischemia treatment with clinically relevant dimensions.
pH-Labile Magnetic Nanocarriers for Intracellular Drug Delivery to Tumor Cells

We report the development of pH-labile ascorbic acid-coated magnetic nanocarriers (AMNCs) for effective delivery of the anticancer drug doxorubicin hydrochloride (DOX) to tumor cells. The uniqueness of this drug delivery system lies in the covalent conjugation of DOX through carbamate and hydrazone bonds, resulting in a slow and sustained drug release profile at different environmental acidities. X-ray diffraction and transmission electron microscopy analyses reveal the formation of crystalline single-phase Fe3O4 nanoparticles with an average size of 10 nm. The changes in the interfacial characteristics of the nanocarriers and the presence of organic coatings are probed by infrared spectroscopy, dynamic light scattering, zeta potential, and thermogravimetric measurements. AMNCs show high colloidal stability in aqueous and cell culture media and possess good magnetic field responsivity and protein resistance characteristics. The drug-loaded nanocarriers exhibited sustained pH-triggered release of drug molecules in acidic mediums, substantial cellular internalization, and significant toxicity toward the proliferation of mouse skin fibrosarcoma (WEHI-164), human breast cancer (MCF-7), and human lung cancer (A549) cells. However, it showed significantly lower toxicity in human normal lung (WI26VA) cells. Overall, these results suggest a pH-sensitive drug release of nanoformulations, which showed selective toxicity to tumor than normal cells.