Prairie View A&M University

Agriculture provides for the most basic needs of humankind: food and fiber. The introduction of new farming techniques in the past century (e.g., during the Green Revolution) has helped agriculture keep pace with growing demands for food and other agricultural products. However, further increases in food demand, a growing population, and rising income levels are likely to put additional strain on natural resources. With growing recognition of the negative impacts of agriculture on the environment, new techniques and approaches should be able to meet future food demands while maintaining or reducing the environmental footprint of agriculture. Emerging technologies, such as geospatial technologies, Internet of Things (IoT), Big Data analysis, and artificial intelligence (AI), could be utilized to make informed management decisions aimed to increase crop production. Precision agriculture (PA) entails the application of a suite of such technologies to optimize agricultural inputs to increase agricultural production and reduce input losses. Use of remote sensing technologies for PA has increased rapidly during the past few decades. The unprecedented availability of high resolution (spatial, spectral and temporal) satellite images has promoted the use of remote sensing in many PA applications, including crop monitoring, irrigation management, nutrient application, disease and pest management, and yield prediction. In this paper, we provide an overview of remote sensing systems, techniques, and vegetation indices along with their recent (2015–2020) applications in PA. Remote-sensing-based PA technologies such as variable fertilizer rate application technology in Green Seeker and Crop Circle have already been incorporated in commercial agriculture. Use of unmanned aerial vehicles (UAVs) has increased tremendously during the last decade due to their cost-effectiveness and flexibility in obtaining the high-resolution (cm-scale) images needed for PA applications. At the same time, the availability of a large amount of satellite data has prompted researchers to explore advanced data storage and processing techniques such as cloud computing and machine learning. Given the complexity of image processing and the amount of technical knowledge and expertise needed, it is critical to explore and develop a simple yet reliable workflow for the real-time application of remote sensing in PA. Development of accurate yet easy to use, user-friendly systems is likely to result in broader adoption of remote sensing technologies in commercial and non-commercial PA applications.

Ever since the agile manifesto was created in 2001, the research community has devoted a great deal of attention to agile software development. This article examines publications and citations to illustrate how the research on agile has progressed in the 10 years following the articulation of the manifesto. Specifically, we delineate the conceptual structure underlying agile scholarship by performing an analysis of authors who have made notable contributions to the field. Further, we summarize prior research and introduce contributions in this special issue on agile software development. We conclude by discussing directions for future research and urging agile researchers to embrace a theory-based approach in their scholarship.

Ionic liquid with acidic properties is an important branch in the wide ionic liquid field and the aim of this article is to cover all aspects of these acidic ionic liquids, especially focusing on the developments in the last four years. The structural diversity and synthesis of acidic ionic liquids are discussed in the introduction sections of this review. In addition, an unambiguous classification system for various types of acidic ionic liquids is presented in the introduction. The physical properties including acidity, thermo-physical properties, ionic conductivity, spectroscopy, and computational studies on acidic ionic liquids are covered in the next sections. The final section provides a comprehensive review on applications of acidic ionic liquids in a wide array of fields including catalysis, CO2 fixation, ionogel, electrolyte, fuel-cell, membrane, biomass processing, biodiesel synthesis, desulfurization of gasoline/diesel, metal processing, and metal electrodeposition.

We study initial-state radiation events, e+ e- --> gammaISR pi+ pi- J/psi, with data collected with the BABAR detector. We observe an accumulation of events near 4.26 GeV/c2 in the invariant-mass spectrum of pi+ pi- J/psi. Fits to the mass spectrum indicate that a broad resonance with a mass of about 4.26 GeV/c2 is required to describe the observed structure. The presence of additional narrow resonances cannot be excluded. The fitted width of the broad resonance is 50 to 90 MeV/c2, depending on the fit hypothesis.

We have observed a narrow state near $2.32\text{ }\mathrm{G}\mathrm{e}\mathrm{V}/{c}^{2}$ in the inclusive ${D}_{s}^{+}{\ensuremath{\pi}}^{0}$ invariant mass distribution from ${e}^{+}{e}^{\ensuremath{-}}$ annihilation data at energies near 10.6 GeV. The observed width is consistent with the experimental resolution. The small intrinsic width and the quantum numbers of the final state indicate that the decay violates isospin conservation. The state has natural spin-parity and the low mass suggests a ${J}^{P}={0}^{+}$ assignment. The data sample corresponds to an integrated luminosity of $91\text{ }{\mathrm{f}\mathrm{b}}^{\ensuremath{-}1}$ recorded by the BABAR detector at the SLAC PEP-II asymmetric-energy ${e}^{+}{e}^{\ensuremath{-}}$ storage ring.

Numerical Techniques in Electromagnetics is designed to show the reader how to pose, numerically analyze, and solve electromagnetic (EM) problems. It gives them the ability to expand their problem-solving skills using a variety of available numerical methods. Topics covered include fundamental concepts in EM; numerical methods; finite difference methods; variational methods, including moment methods and finite element methods; transmission-line matrix or modeling (TLM); and Monte Carlo methods. The simplicity of presentation of topics throughout the book makes this an ideal text for teaching or self-study by senior undergraduates, graduate students, and practicing engineers.

The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one. This radical change has shaken existing farming techniques and produced the latest prospects in a series of challenges. This comprehensive review article enlightens the potential of the IoT in the advancement of agriculture and the challenges faced when combining these advanced technologies with conventional agricultural systems. A brief analysis of these advanced technologies with sensors is presented in advanced agricultural applications. Numerous sensors that can be implemented for specific agricultural practices require best management practices (e.g., land preparation, irrigation systems, insect, and disease management). This review includes the integration of all suitable techniques, from sowing to harvesting, packaging, transportation, and advanced technologies available for farmers throughout the cropping system. Besides, this review article highlights the utilization of other tools such as unmanned aerial vehicles (UAVs) for crop monitoring and other beneficiary measures, such as optimizing crop yields. In addition, advanced programs based on the IoT are also discussed. Finally, based on our comprehensive review, we identified advanced prospects regarding the IoT, which are essential tools for sustainable agriculture.

We study the decay B- --> J/psi K- pi+ pi- using 117 million BBbar events collected at the Y(4S) resonance with the BaBar detector at the PEP-II e+ e- asymmetric-energy storage ring. We measure the branching fractions Br(B- --> J/psi K- pi+ pi-) = (116 +- 7 (stat.) +- 9(syst.))* 10-5 and Br(B- --> X(3872)K-)* Br (X(3872) --> J/psi pi+ pi-) =(1.28+- 0.41)* 10-5 and find the mass of the X(3872) to be 3873.4 +- 1.4 MeV/c2. We search for the h_c narrow state in the decay B- --> h_c K-, h_c --> J/psi pi+ pi- and for the decay B- --> J/psi D0 pi-, with D0 --> K- pi+. We set the 90% C.L. limits Br(B- --> h_c K-)* Br (h_c --> J/psi pi+ pi-) <3.4 * 10-6 and Br(B- --> J/psi D0 pi-) <5.2 * 10-5.

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ABSTRACT This paper examines the impact of hedge fund activism on corporate tax avoidance. We find that relative to matched control firms, businesses targeted by hedge fund activists exhibit lower tax avoidance levels prior to hedge fund intervention, but experience increases in tax avoidance after the intervention. Moreover, findings suggest that the increase in tax avoidance is greater when activists have a successful track record of implementing tax changes and possess tax interest or knowledge as indicated by their Securities and Exchange Commission (SEC) 13D filings. We also find that these greater tax savings do not appear to result from an increased use of high-risk and potentially illegal tax strategies, such as sheltering. Taken together, the results suggest that shareholder monitoring of firms, in the form of hedge fund activism, improves tax efficiency. JEL Classifications: G32; G34; H26. Data Availability: Data are available from sources identified in the text.

BACKGROUND: As a result of advances in skin imaging technology and the development of suitable image processing techniques, during the last decade, there has been a significant increase of interest in the computer-aided diagnosis of melanoma. Automated border detection is one of the most important steps in this procedure, because the accuracy of the subsequent steps crucially depends on it. METHODS: In this article, we present a fast and unsupervised approach to border detection in dermoscopy images of pigmented skin lesions based on the statistical region merging algorithm. RESULTS: The method is tested on a set of 90 dermoscopy images. The border detection error is quantified by a metric in which three sets of dermatologist-determined borders are used as the ground-truth. The proposed method is compared with four state-of-the-art automated methods (orientation-sensitive fuzzy c-means, dermatologist-like tumor extraction algorithm, meanshift clustering, and the modified JSEG method). CONCLUSION: The results demonstrate that the method presented here achieves both fast and accurate border detection in dermoscopy images.

The traditional goal of optimization and control is making way for learning and innovation.

Despite growing interest in the visible light‐absorbing organic component of atmospheric aerosols, referred to as “brown” carbon, our knowledge of its chemical composition remains limited. It is well accepted that biomass burning is one important source of “brown” carbon in the atmosphere. In this study, cloud water samples heavily affected by biomass burning were collected at Mount Tai (1534 m, ASL), located in Shandong province in the North China Plain in summer 2008. The samples were analyzed with high performance liquid chromatography equipped with a UV/Vis absorbance detector immediately followed by electrospray ionization and analysis using a time‐of‐flight (ToF) mass spectrometer. The high mass resolution and accuracy provided by the ToF mass spectrometer allow determination of the elemental composition of detected ions. Using this approach, the elemental compositions of 16 major light‐absorbing compounds, which together accounted for approximately half of measured sample absorption between 300 and 400 nm, were determined. The most important classes of light‐absorbing compounds were found to be nitrophenols and aromatic carbonyls. Light absorption over this wavelength range by reduced nitrogen compounds was insignificant in these samples.

The modern requirement for analyzing and interpreting ever-larger volumes of seismic data to identify prospective hydrocarbon prospects within stringent time deadlines represents an ongoing challenge in petroleum exploration. To provide a computer-based aid in addressing this challenge, we have developed a “big data” platform to facilitate the work of geophysicists in interpreting and analyzing large volumes of seismic data with scalable performance. We have constructed this platform on a modern distributed-memory infrastructure, providing a customized seismic analytics software development toolkit, and a Web-based graphical workflow interface along with a remote 3D visualization capability. These support the management of seismic data volumes, attributes processing, seismic analytics model development, workflow execution, and 3D volume visualization on a scalable, distributed computing platform. Early experiences show that computationally demanding deep learning methods such as convolutional neural networks (CNN) provide improved results over traditional methods such as support vector machines (SVMs) and logistic regression for identifying geologic faults in 3D seismic volumes. Our experiments show encouraging accuracy in identifying faults by combining CNN and traditional machine learning models with a variety of seismic attributes, and the platform is able to deliver scalable performance.

Linguistics is concerned with rules that are followed by languages as a system. Computational linguistics(CL)combines the power of machine learning and human language.As a subfield of linguistics, CL is concerned with the computational description of rules that languages follow. Itis what powers anything in a machine or device that has to do with language—speaking, writing, reading, and listening. It is often linked with natural language processing (NLP), which is the use of computers to identify structures in natural language.The boundary between NLP and CL is not so clear-cut. This paper is a primer on computational linguistics

We present a measurement of the cross section of the process ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}\ensuremath{\psi}(2S)$ from threshold up to 8 GeV center-of-mass energy using events containing initial-state radiation, produced at the SLAC PEP-II ${e}^{+}{e}^{\ensuremath{-}}$ storage rings. The study is based on $298\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of data recorded with the BABAR detector. A structure is observed in the cross section not far above threshold, near 4.32 GeV. We also investigate the compatibility of this structure with the $Y(4260)$ previously reported by this experiment.

This study examines long-run relationships and short-run dynamic causal linkages among the US, Japanese, and ten Asian emerging stock markets, with the particular attention to the 1997–1998 Asian financial crisis. Extending related empirical studies, comparative analyses of pre-crisis, crisis, and post-crisis periods are conducted to comprehensively evaluate how stock market integration is affected by financial crises. In general, the results for the case of Asia show that both long-run cointegration relationships and short-run causal linkages among these markets were strengthened during the crisis and that these markets have generally been more integrated after the crisis than before the crisis. Detailed country-by-country analyses are provided, which yield a variety of new results concerning the roles of individual countries in international stock market integration. An important implication of our findings is that the degree of integration among countries tends to change over time, especially around periods marked by financial crises.

We present results on time-dependent $CP$ asymmetries in neutral $B$ decays to several $CP$ eigenstates. The measurements use a data sample of about $88\ifmmode\times\else\texttimes\fi{}{10}^{6}$ $\ensuremath{\Upsilon}(4S)\ensuremath{\rightarrow}B\overline{B}$ decays collected between 1999 and 2002 with the BABAR detector at the PEP-II asymmetric-energy $B$ factory at SLAC. We study events in which one neutral $B$ meson is fully reconstructed in a final state containing a charmonium meson and the other $B$ meson is determined to be either a ${B}^{0}$ or ${\overline{B}}^{0}$ from its decay products. The amplitude of the $CP$ asymmetry, which in the standard model is proportional to $\mathrm{sin}2\ensuremath{\beta}$, is derived from the decay-time distributions in such events. We measure $\mathrm{sin}2\ensuremath{\beta}=0.741\ifmmode\pm\else\textpm\fi{}0.067\mathrm{(}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{t}\mathrm{)}\ifmmode\pm\else\textpm\fi{}0.034\mathrm{(}\mathrm{s}\mathrm{y}\mathrm{s}\mathrm{t}\mathrm{)}$ and $|\ensuremath{\lambda}|=0.948\ifmmode\pm\else\textpm\fi{}0.051\mathrm{(}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{t}\mathrm{)}\ifmmode\pm\else\textpm\fi{}0.030\mathrm{(}\mathrm{s}\mathrm{y}\mathrm{s}\mathrm{t}\mathrm{)}$. The magnitude of $\ensuremath{\lambda}$ is consistent with unity, in agreement with the standard model expectation of no direct $CP$ violation in these modes.

We live and operate in the world of computing and computers. The Internet has drastically changed the computing world from the concept of parallel computing to distributed computing to grid computing and now to cloud computing. Cloud computing is a new wave in the field of information technology. Some see it as an emerging field in computer science. It consists of a set of resources and services offered through the Internet. Hence, ?cloud computing? is also called ?Internet computing.? The word ?cloud? is a metaphor for describing the Web as a space where computing has been preinstalled and exists as a service. Operating systems, applications, storage, data, and processing capacity all exist on the Web, ready to be shared among users. Figure 1 shows a conceptual diagram of cloud computing.

The Boussinesq equation simulates weakly nonlinear and long wave approximation that can be used in water waves, coastal engineering, and numerical models for water wave simulation in harbors and shallow seas. In this article, the sine-Gordon expansion (SGE) approach and the generalized Kudryashov (GK) scheme are used to establish broad-spectral solutions including unknown parameters and typical analytical solutions are recovered as a special case. The well-known bell-shape soliton, kink, singular kink, compacton, contracted bell-shape soliton, periodic soliton, anti-bell shape soliton, and other shape solitons are retrieved for the definite value of these constraints. The 3D and contour plots of some of the results obtained are sketched by assigning individual values of the parameter and analyzed the dynamical behavior of the waves. Furthermore, the compatibility of the two approaches has been compared and examined the efficiency to ascertain soliton solutions.