North Carolina Agricultural and Technical State University

SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT, including manual calibration procedures and automated procedures using the shuffled complex evolution method and other common methods. In addition, SWAT-CUP was recently developed and provides a decision-making framework that incorporates a semi-automated approach (SUFI2) using both manual and automated calibration and incorporating sensitivity and uncertainty analysis. In SWAT-CUP, users can manually adjust parameters and ranges iteratively between autocalibration runs. Parameter sensitivity analysis helps focus the calibration and uncertainty analysis and is used to provide statistics for goodness-of-fit. The user interaction or manual component of the SWAT-CUP calibration forces the user to obtain a better understanding of the overall hydrologic processes (e.g., baseflow ratios, ET, sediment sources and sinks, crop yields, and nutrient balances) and of parameter sensitivity. It is important for future calibration developments to spatially account for hydrologic processes; improve model run time efficiency; include the impact of uncertainty in the conceptual model, model parameters, and measured variables used in calibration; and assist users in checking for model errors. When calibrating a physically based model like SWAT, it is important to remember that all model input parameters must be kept within a realistic uncertainty range and that no automatic procedure can substitute for actual physical knowledge of the watershed.

This paper presents a treatment of discrete variable structure control systems. The purpose is to lay a foundation upon which design of such type of systems can be made properly. Phenomena of switching, reaching, and quasi-sliding mode are investigated thoroughly. Terms pertaining to discrete variable structure control are defined. A method of quasi-sliding mode design is given. The inherently existing quasi-sliding mode band is analyzed. A recently introduced "reaching law approach" is conveniently used to develop the control law for robust control. Comments are given regarding chattering. The design technique is illustrated by a simulated system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Agricultural soils in the southeastern U.S. Coastal Plain region have meager soil fertility characteristics because of their sandy textures, acidic pH values, kaolinitic clays, low cation exchange capacities, and diminutive soil organic carbon contents. We hypothesized that biochar additions will help ameliorate some of these fertility problems. The study objectives were to determine the impact of pecan shell-based biochar additions on soil fertility characteristics and water leachate chemistry for a Norfolk loamy sand (fine-loamy, kaolinitic, thermic typic Kandiudults). Soil columns containing 0, 0.5, 1.0, and 2.0% (wt/wt) biochar were incubated at 10% (wt/wt) moisture for 67 days. On days 25 and 67, the columns were leached with 1.2 to 1.4 pore volumes of deionized H2O, and the leachate chemical composition determined. On days 0 and 67, soil samples were collected and analyzed for fertility. The biochar had a pH of 7.6, contained 834.2 and 3.41 g kg−1 of C and N, respectively, and was dominated by aromatic C (58%). After 67 days and two leaching events, biochar additions to the Norfolk soil increased soil pH, soil organic carbon, Ca, K, Mn, and P and decreased exchangeable acidity, S, and Zn. Biochar additions did not significantly increase soil cation exchange capacity. Leachates contained increasing electrical conductivity and K and Na concentrations, but decreasing levels of Ca, P, Mn, and Zn. These effects reflect the addition of elements and the higher sorption capacity of biochar for selective nutrients (especially Ca, P, Zn, and Mn). Biochar additions to the Norfolk soil caused significant fertility improvements.

The noise sensitivities for nine different QRS detection algorithms were measured for a normal, single-channel lead II, synthesized ECG corrupted with five different types of synthesized noise. The noise types were electromyographic interference, 60 Hz powerline interference, baseline drift due to respiration, abrupt baseline shift, and a composite noise constructed from all of the other noise types. The percentage of QRS complexes detected, the number of false positives, and the detection delay were measured. None of the algorithms were able to detect all QRS complexes without any false positives for all of the noise types at the highest noise level. Algorithms based on amplitude and slope had the highest performance for EMG-corrupted ECG. An algorithm using a digital filter had the best performance for the composite noise corrupted data.

Sonochemical engineering is a field involving the application of sonic and ultrasonic waves to chemical processing. Sonochemistry enhances or promotes chemical reactions and mass transfer. It offers the potential for shorter reaction cycles, cheaper reagents, and less extreme physical conditions, leading to less expensive and perhaps smaller plants. The amount of things that can be accomplished with sonochemistry is, at this stage, only limited by the minds of those working in this exciting field. Existing literature on sonochemical reacting systems is chemistry-intensive, and applications of this novel means of reaction in environmental remediation and pollution prevention seem almost unlimited. For example, environmental sonochemistry is a rapidly growing area that deals with the destruction of organics in aqueous solutions. However, some theoretical and engineering aspects are not fully understood. This paper reviews the field comprehensively by combining the existing knowledge from chemistry with insights into the pathways and kinetic analysis of environmental sonochemical reacting systems and with challenges for large-scale applications. The review is intended to advance our understanding and outline directions for future research.

Thermal stability of charged LiNixMnyCozO2 (NMC, with x + y + z = 1, x:y:z = 4:3:3 (NMC433), 5:3:2 (NMC532), 6:2:2 (NMC622), and 8:1:1 (NMC811)) cathode materials is systematically studied using combined in situ time-resolved X-ray diffraction and mass spectroscopy (TR-XRD/MS) techniques upon heating up to 600 °C. The TR-XRD/MS results indicate that the content of Ni, Co, and Mn significantly affects both the structural changes and the oxygen release features during heating: the more Ni and less Co and Mn, the lower the onset temperature of the phase transition (i.e., thermal decomposition) and the larger amount of oxygen release. Interestingly, the NMC532 seems to be the optimized composition to maintain a reasonably good thermal stability, comparable to the low-nickel-content materials (e.g., NMC333 and NMC433), while having a high capacity close to the high-nickel-content materials (e.g., NMC811 and NMC622). The origin of the thermal decomposition of NMC cathode materials was elucidated by the changes in the oxidation states of each transition metal (TM) cations (i.e., Ni, Co, and Mn) and their site preferences during thermal decomposition. It is revealed that Mn ions mainly occupy the 3a octahedral sites of a layered structure (R3̅m) but Co ions prefer to migrate to the 8a tetrahedral sites of a spinel structure (Fd3̅m) during the thermal decomposition. Such element-dependent cation migration plays a very important role in the thermal stability of NMC cathode materials. The reasonably good thermal stability and high capacity characteristics of the NMC532 composition is originated from the well-balanced ratio of nickel content to manganese and cobalt contents. This systematic study provides insight into the rational design of NMC-based cathode materials with a desired balance between thermal stability and high energy density.

Biochar additions to degraded soils have the potential to improve crop yield and soil quality. We hypothesize that the biochar production process can be tailored to form designer biochars that have specific chemical characteristics matched to selective chemical and/or physical issues of a degraded soil. We produced biochars from peanut hulls, pecan shells, poultry litter, and switchgrass at temperatures ranging from 250oC to 700oC. Biochars were characterized

This paper presents an application of genetic algorithms (GAs) to nonlinear constrained optimization. GAs are general purpose optimization algorithms which apply the rules of natural genetics to explore a given search space. When GAs are applied to nonlinear constrained problems, constraint handling becomes an important issue. The proposed search algorithm is realized by GAs which utilize a penalty function in the objective function to account for violation. This extension is based on systematic multi-stage assignments of weights in the penalty method as opposed to single-stage assignments in sequential unconstrained minimization. The experimental results are satisfactory and agree well with those of the gradient type methods.

Sentiment analysis or opinion mining is one of the major tasks of NLP (Natural Language Processing). Sentiment analysis has gain much attention in recent years. In this paper, we aim to tackle the problem of sentiment polarity categorization, which is one of the fundamental problems of sentiment analysis. A general process for sentiment polarity categorization is proposed with detailed process descriptions. Data used in this study are online product reviews collected from Amazon.com. Experiments for both sentence-level categorization and review-level categorization are performed with promising outcomes. At last, we also give insight into our future work on sentiment analysis.

PURPOSE: Exercise is associated with altered gut microbial composition, but studies have not investigated whether the gut microbiota and associated metabolites are modulated by exercise training in humans. We explored the impact of 6 wk of endurance exercise on the composition, functional capacity, and metabolic output of the gut microbiota in lean and obese adults with multiple-day dietary controls before outcome variable collection. METHODS: Thirty-two lean (n = 18 [9 female]) and obese (n = 14 [11 female]), previously sedentary subjects participated in 6 wk of supervised, endurance-based exercise training (3 d·wk) that progressed from 30 to 60 min·d and from moderate (60% of HR reserve) to vigorous intensity (75% HR reserve). Subsequently, participants returned to a sedentary lifestyle activity for a 6-wk washout period. Fecal samples were collected before and after 6 wk of exercise, as well as after the sedentary washout period, with 3-d dietary controls in place before each collection. RESULTS: β-diversity analysis revealed that exercise-induced alterations of the gut microbiota were dependent on obesity status. Exercise increased fecal concentrations of short-chain fatty acids in lean, but not obese, participants. Exercise-induced shifts in metabolic output of the microbiota paralleled changes in bacterial genes and taxa capable of short-chain fatty acid production. Lastly, exercise-induced changes in the microbiota were largely reversed once exercise training ceased. CONCLUSION: These findings suggest that exercise training induces compositional and functional changes in the human gut microbiota that are dependent on obesity status, independent of diet and contingent on the sustainment of exercise.

With current intensive agriculture practices and industrialization, pollution of natural resources like land and water with heavy metals, organic pollutants, radionuclides, pesticides, and fertilizers has become a major concern. Phytoremediation is a cost-effective and environmentally friendly technique that utilizes plants to immobilize, uptake, reduce toxicity, stabilize, or degrade the compounds that are released into the environment from different sources. Studies have shown that heavy metals, organic contaminants, radionuclides, antibiotics, and pesticides can be remediated using plants. Though phytoremediation has been practiced since decades, it is still an emerging technology. This review article summarizes existing information and synthesizes the recent findings on plant species suitable for use in phytoremediation through utilizing different mechanisms, aids that can enhance the efficiency of phytoremediation processes, and strengths and limitations that comes with the application of this technique. Diverse plants remediate different pollutants at different rates through one or multiple mechanisms. The limitations of phytoremediation can be overcome by using several aids including natural and chemical amendments, genetic engineering and natural microbial stimulation. Given the low-cost of phytoremediation compared to conventional technology and sustainability associated with plants and use of renewable energy, phytoremediation can be a reliable solution for a sustainable and economical remediation of soil and water from the organic and inorganic pollutants.

This paper examines the applicability of genetic algorithms (GA's) in the simultaneous design of membership functions and rule sets for fuzzy logic controllers. Previous work using genetic algorithms has focused on the development of rule sets or high performance membership functions; however, the interdependence between these two components suggests a simultaneous design procedure would be a more appropriate methodology. When GA's have been used to develop both, it has been done serially, e.g., design the membership functions and then use them in the design of the rule set. This, however, means that the membership functions were optimized for the initial rule set and not the rule set designed subsequently. GA's are fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. This new method has been applied to two problems, a cart controller and a truck controller. Beyond the development of these controllers, we also examine the design of a robust controller for the cart problem and its ability to overcome faulty rules.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

we present an exact and interactive collision detection system, I-COLLIDE, for large-scale environments. Such environments are characterized by the number of objects undergoing rigid motion and the complexity of the models. The algorithm does not assume the objects' motions can be expressed as a closed form function of time. The collision detection system is general and can be easily interfaced with a variety of applications. The algorithm uses a two-level approach based on pruning multiple-object pairs using bounding boxes and performing exact collision detection between selected pairs of polyhedral models. We demonstrate the performance of the system in walkthrough and simulation environments consisting of a large number of moving objects. In particular, the system takes less than 1/20 of a second to determine all the collisions and contacts in an environment consisting of more than 1000 moving polytopes, each consisting of more than 50 faces on an HP-9000/750.

Internet of Things (IoT) and smart computing technologies have revolutionized every sphere of 21 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> century humans. IoT technologies and the data driven services they offer were beyond imagination just a decade ago. Now, they surround us and influence a variety of domains such as automobile, smart home, healthcare, etc. In particular, the Agriculture and Farming industries have also embraced this technological intervention. Smart devices are widely used by a range of people from farmers to entrepreneurs. These technologies are used in a variety of ways, from finding real-time status of crops and soil moisture content to deploying drones to assist with tasks such as applying pesticide spray. However, the use of IoT and smart communication technologies introduce a vast exposure to cybersecurity threats and vulnerabilities in smart farming environments. Such cyber attacks have the potential to disrupt the economies of countries that are widely dependent on agriculture. In this paper, we present a holistic study on security and privacy in a smart farming ecosystem. The paper outlines a multi layered architecture relevant to the precision agriculture domain and discusses the security and privacy issues in this dynamic and distributed cyber physical environment. Further more, the paper elaborates on potential cyber attack scenarios and highlights open research challenges and future directions.

Food quality came out as the only one of nine factors being tested that had a significant effect on intent to return for 239 diners at an Irish-pub-style full-service restaurant in the southeastern United States. Even so, food provided only a partial explanation of the repeat-patronage decision. Examining customer satisfaction, food quality again was at the top of the list, but the restaurant’s atmosphere and the fairness of the seating procedures also had significant effects. Together, those three factors explained about half of the variability in a regression model of customer satisfaction. Given that food was such a strong factor in the repeat-patronage decision, diners’ suggestions to this restaurant are of interest to other restaurateurs. The diners suggested that the restaurant expand its menu. In particular, they wanted to see more items that fit the restaurant’s Irish-pub theme. Finally, diners were especially interested in having additional healthful menu items.

The purpose of this study was to better understand the instructional and assessment strategies that are most effective in the online learning environment. Faculty and students identified several strategies for maintaining instructional quality in the online environment, including the importance of using a variety of instructional methods to appeal to various learning styles and building an interactive and cohesive learning environment that includes group work. Online assessment strategies include having a wide variety of clearly explained assignments on a regular basis and providing meaningful and timely feedback to students regarding the quality of their work. Effective assessment techniques include projects, portfolios, self-assessments, peer evaluations, and weekly assignments with immediate feedback. The role of meaningful feedback cannot be overemphasized.

Plants will be an important component of future long-term space missions. Lighting systems for growing plants will need to be lightweight, reliable, and durable, and light-emitting diodes (LEDs) have these characteristics. Previous studies demonstrated that the combination of red and blue light was an effective light source for several crops. Yet the appearance of plants under red and blue lighting is purplish gray making visual assessment of any problems difficult. The addition of green light would make the plant leave appear green and normal similar to a natural setting under white light and may also offer a psychological benefit to the crew. Green supplemental lighting could also offer benefits, since green light can better penetrate the plant canopy and potentially increase plant growth by increasing photosynthesis from the leaves in the lower canopy. In this study, four light sources were tested: 1) red and blue LEDs (RB), 2) red and blue LEDs with green fluorescent lamps (RGB), 3) green fluorescent lamps (GF), and 4) cool-white fluorescent lamps (CWF), that provided 0%, 24%, 86%, and 51% of the total PPF in the green region of the spectrum, respectively. The addition of 24% green light (500 to 600 nm) to red and blue LEDs (RGB treatment) enhanced plant growth. The RGB treatment plants produced more biomass than the plants grown under the cool-white fluorescent lamps (CWF treatment), a commonly tested light source used as a broad-spectrum control.

Piper species are aromatic plants used as spices in the kitchen, but their secondary metabolites have also shown biological effects on human health. These plants are rich in essential oils, which can be found in their fruits, seeds, leaves, branches, roots and stems. Some Piper species have simple chemical profiles, while others, such as Piper nigrum, Piper betle, and Piper auritum, contain very diverse suites of secondary metabolites. In traditional medicine, Piper species have been used worldwide to treat several diseases such as urological problems, skin, liver and stomach ailments, for wound healing, and as antipyretic and anti-inflammatory agents. In addition, Piper species could be used as natural antioxidants and antimicrobial agents in food preservation. The phytochemicals and essential oils of Piper species have shown strong antioxidant activity, in comparison with synthetic antioxidants, and demonstrated antibacterial and antifungal activities against human pathogens. Moreover, Piper species possess therapeutic and preventive potential against several chronic disorders. Among the functional properties of Piper plants/extracts/active components the antiproliferative, anti-inflammatory, and neuropharmacological activities of the extracts and extract-derived bioactive constituents are thought to be key effects for the protection against chronic conditions, based on preclinical in vitro and in vivo studies, besides clinical studies. Habitats and cultivation of Piper species are also covered in this review. In this current work, available literature of chemical constituents of the essential oils Piper plants, their use in traditional medicine, their applications as a food preservative, their antiparasitic activities and other important biological activities are reviewed.

There is a greater demand for antimicrobial finishes on textile goods because consumers have become aware of the potential advantages of these materials. A number of other chemicals are also used i...

IMPORTANCE: Genetic variants associated with susceptibility to late-onset Alzheimer disease are known for individuals of European ancestry, but whether the same or different variants account for the genetic risk of Alzheimer disease in African American individuals is unknown. Identification of disease-associated variants helps identify targets for genetic testing, prevention, and treatment. OBJECTIVE: To identify genetic loci associated with late-onset Alzheimer disease in African Americans. DESIGN, SETTING, AND PARTICIPANTS: The Alzheimer Disease Genetics Consortium (ADGC) assembled multiple data sets representing a total of 5896 African Americans (1968 case participants, 3928 control participants) 60 years or older that were collected between 1989 and 2011 at multiple sites. The association of Alzheimer disease with genotyped and imputed single-nucleotide polymorphisms (SNPs) was assessed in case-control and in family-based data sets. Results from individual data sets were combined to perform an inverse variance-weighted meta-analysis, first with genome-wide analyses and subsequently with gene-based tests for previously reported loci. MAIN OUTCOMES AND MEASURES: Presence of Alzheimer disease according to standardized criteria. RESULTS: Genome-wide significance in fully adjusted models (sex, age, APOE genotype, population stratification) was observed for a SNP in ABCA7 (rs115550680, allele = G; frequency, 0.09 cases and 0.06 controls; odds ratio [OR], 1.79 [95% CI, 1.47-2.12]; P = 2.2 × 10(-9)), which is in linkage disequilibrium with SNPs previously associated with Alzheimer disease in Europeans (0.8 < D' < 0.9). The effect size for the SNP in ABCA7 was comparable with that of the APOE ϵ4-determining SNP rs429358 (allele = C; frequency, 0.30 cases and 0.18 controls; OR, 2.31 [95% CI, 2.19-2.42]; P = 5.5 × 10(-47)). Several loci previously associated with Alzheimer disease but not reaching significance in genome-wide analyses were replicated in gene-based analyses accounting for linkage disequilibrium between markers and correcting for number of tests performed per gene (CR1, BIN1, EPHA1, CD33; 0.0005 < empirical P < .001). CONCLUSIONS AND RELEVANCE: In this meta-analysis of data from African American participants, Alzheimer disease was significantly associated with variants in ABCA7 and with other genes that have been associated with Alzheimer disease in individuals of European ancestry. Replication and functional validation of this finding is needed before this information is used in clinical settings.