Jniz 2.3

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Also, something interesting that we can notice is that we’re getting two parameters passed to our function; a pointer to the current JNIEnv; and also the Java object that the method is attached to, the instance of our HelloWorldJNI class. Now, we have to create a new. We’ll name our. Compiling And Linking At this point, we have all parts we need in place and have a connection between them. Ubuntu version: Whatever we decide to name it is the argument passed into the method System.

Jniz 2.3

We can now run our program from the command line. However, we need to add the full path to the directory containing the library we’ve just generated. This way Java will know where to look for our native libs: Let’s create a new class called ExampleParametersJNI with two native methods using parameters and returns of different types: Now create the corresponding. The numbers received are: To test our code, we’ve to repeat all the compilation steps of the previous HelloWorld example.

We’ll start creating a new class UserData that we’ll use to store some user info: Normally, we just need to provide the full class name to access a Java class, or the correct method name and signature to access an object method. We’re even creating an instance of the class com.

UserData in our native code. Repeat to create a target “clean”. Step 5: However, you need to provide the library path to the “hello. This can be done via VM argument -Djava. You shall see the output “Hello World!

Java Primitives: Java Reference Types: It also defines the following sub-types: Java array is a reference type with eight primitive array and one Object array.

Hence, there are eight array of primitives jintArray, jbyteArray, jshortArray, jlongArray, jfloatArray, jdoubleArray, jcharArray and jbooleanArray; and one object array jobjectArray. However, native functions operate on their own native types such as C-string, C’s int[]. Hence, there is a need to convert or transform between JNI types and the native types.

The native programs: Receive the arguments in JNI type passed over by the Java program. For reference JNI type, convert or copy the arguments to local native types, e. Primitive JNI types such as jint and jdouble do not need conversion and can be operated directly. Perform its operations, in local native type. Create the returned object in JNI type, and copy the result into the returned object. The most confusing and challenging task in JNI programming is the conversion or transformation between JNI reference types such as jstring, jobject, jintArray, jobjectArray and native types C-string, int[].

The JNI Environment interface provides many functions to do the conversion. JNI is a C interface, which is not object-oriented. It does not really pass the objects. A jxxx type is defined in the native system, i. Java JNI Program: It declares a native method average that receives two int’s and returns a double containing the average value of the two int’s. The main method invoke the average. The “jni. It is interesting to note that jint is mapped to C’s long which is at least 32 bits , instead of of C’s int which could be 16 bits.

Hence, it is important to use jint in the C program, instead of simply using int. The main method invokes the sayHello. The return-type is also jstring. Passing strings is more complicated than passing primitives, as Java’s String is an object reference type , while C-string is a NULL-terminated char array. It then performs its intended operations – displays the string received and prompts user for another string to be returned. Perform its intended operations printf “In C, the received string is: Hello from Java Enter a String: The JNI string jstring functions are: String object from an array of characters in modified UTF-8 encoding.

String object from an array of Unicode characters. The function returns NULL if the memory cannot be allocated. It is always a good practice to check against NULL. String instance. The JNI runtime will try to return a direct pointer, if possible; otherwise, it returns a copy.

Nonetheless, we seldom interested in modifying the underlying string, and often pass a NULL pointer. JDK 1. The isCopy is not needed as the C’s array is pre-allocated. For detailed description, always refer to “Java Native Interface Specification” http: There are 9 types of Java arrays, one each of the eight primitives and an array of java.

JNI defines a type for each of the eight Java primitive arrays, i. It also define a jobjectArray for Java’s array of Object to be discussed later. Again, you need to convert between JNI array and native array, e. The JNI Environment interface provides a set of functions for the conversion: There are 8 sets of the above functions, one for each of the eight Java primitives.

The native program is required to: But please also note that an even better suggestion was made by Mary Barber, former executive leader with the Ecological Society of America’s Executive, who opposed the ” Point 2 EPA should also guard against the tendency to give undue emphasis to “Data Quality Objectives” in the selection and evaluation of instruments and subsequent implementation of field measurement programs to the exclusion of concern about “Science Quality Objectives” and “Policy Relevancy Objectives.

Please find attached to this E-mail message, an electronic version of these Guidelines which we have adopted and very slightly adapted for use in formulating policy relevant scientific findings in the Southern Oxidants Study. As indicated in Appendix III: These guidelines may have broader utility in other programs at the interface of science and public policy and are presented here with that potential use in mind. Ellis B. Given the substantial expertise of many of the subcommittee members on the technical details of the sampling methods, my comments are intentionally of a more general nature, and specifically encourage EPA to consider the many important objectives of a new PMc sampling program – in addition to determining compliance with anticipated new standards.

In hindsight, this didn’t work out so well – and I’d like to try to clarify some of these points. Since crustal material i. I don’t agree with this emphasis in the current draft CD chapters, think that it is overstated in a speculative manner, and have submitted supplemental comments on this issue copy attached at bottom of these NAAMM comments.

Those health studies that have specifically attempted to evaluate effects of coarse particles have shown a wide range of potential responses – ranging from illogical negative associations with mortality, to large positive associations that exceed those for fine particles.

Although it is currently unclear what level s or averaging time s will be proposed for a PMc standard s , a reasonable assumption is that there will not be high confidence that any specific level of standard will represent a clear “bright line” above and below which effects do and don’t occur. Given the anticipated high degree of spatial and temporal variability of ambient PMc concentrations compared to PM2. For these reasons, I suggest that the always important monitoring objective of determining compliance with standards is of relatively less importance for PMc than it is for many other criteria pollutants PMs.

Conversely, other measurement objectives take on relatively greater importance and should be carefully considered. Virtually all past studies that have jointly considered health effects of fine and coarse particles have employed methods that are more precise for PM2. For these reasons, an especially important objective of new PMc measurements should be to collocate precise PMc and PM2. Given the anticipated high degree of temporal variability in PMc vs. For the most part, the chemical composition of coarse particles has not, historically, been well characterized typically done by subtraction or dicot if at all and this would seem like a third important objective.

For this reason, methods that allow collection of coarse-only particles on filter media suitable for chemical analyses should also be emphasized. For this reason, I encourage EPA to consider reanalysis by other labs and methods of the coarse dicot filters or maybe the PM and 2. Potentially, the use of such denuders would be most important for hour filter-based methods and less critical for “fast response” continuous methods. Given the above-stated current uncertainties in absolute “bright line” PMc concentrations which are injurious, the high temporal variability, and the greater artifact potential, I don’t think it’s absolutely necessary and perhaps not desirable to have a filter-based FRM for PMc.

Some consideration should be given to specifying a continuous method as the FRM, with a filter method as FEM, specifically intended for subsequent speciation analyses at a limited number of sites.

For various reasons, developing a much better understanding of the biological content of coarse particles seems especially important. Its unclear to me if there are currently available analyses that could reveal key biological indicators from filter-based samples on a “routine” basis, but I would suggest EPA devote some research into potential, low-cost “biological indicator” analyses that might be conducted on “routine” PMc filter samples protein, carbohydrates, etc.

It can be reasonably assumed in advance that PMc will exhibit a high degree of spatial variability especially for locally generated particles – PMc from more distant sources like African or Asian dust storms will be more spatially uniform.

Characterizing PMc spatial patterns can’t be done by measurements alone, and development of better microscale models should be considered an important objective. Better quantification of the full range of coarse particle size distributions including above 10 um such as by optical particle counters will also be helpful.

Careful attention to monitor siting characteristics, especially inlet height and distance from roadways, agricultural and mining activities will also be critical. Focused gradient studies how rapidly do concentrations fall off with distance from roadways? But such “experiments” do not need to be repeated everywhere, and consideration should be given to identifying a small number of more intensive sites in each region of the country. Possibly such sites could be periodically “rotated” among states in a region to avoid disruption of state-specific monitoring funds.

While filter-based measurements of PM2. Some consideration should be given to coordination between the toxics and PMc programs, to at least allow for use of subtraction of precise samples at sites where such measurements are being conducted already. In addition, for sites where PM2. Along similar lines, is there any possibility of modifying inlets of existing PM2.

My sense is the PM2. B-9 [The following is also included at the request of Mr. These discussions are clear, detailed, helpful and informative – and I think the results could conceptually be presented, integrated, summarized, etc. Based on discussions at the CASAC PM CD review, subsequent discussions at the PM coarse monitoring methods review and on a re-reading of relevant sections of chapters 8 and 9,1 encourage EPA to more heavily emphasize the former 1 use of this information and de- emphasize the latter 2.

General reasons include: Taken in the aggregate, they clearly show adverse effects from many species, but individually no one study is definitive. These results are then often further interpreted and commented on in the CD in a highly speculative manner.

Specifically, I think the chapter 9 integrated synthesis should de-emphasize or present counter examples in sections where specific source categories are identified as uniquely benign. This seems most evident for the contributions of “crustal” emissions to PM2. Here, it’s not entirely clear why this is “of much importance” compared to what? The consistent finding of a negative association and implication we would live longer if it were dustier is a consistent indication to me of a poorly formulated model s.

It is also inconsistent with the many studies mostly cited in the CD which do show effects associated with coarse particle mass, and with the rather extensive bodies of literature on adverse effects from both the inorganic components of crustal material silicosis, pneumoconiosis, etc. I’ve listed some references grouped in these 3 general areas at the end of these comments. Several features of the rather outdated receptor model approach taken by the studies which I assume are referred to in “all of the above studies” are important.

First, all multi-elemental measurement techniques, and especially the most common XRF, coincidentally quantify a large number of elements which are of predominantly crustal origin Si, Al, Fe, Ca, Ti, etc. For this reason, a “crustal” or “soil” factor is nearly always identified in virtually all receptor model applications.

The rotated eigenvector factor analysis approach which I think was used in all of the above studies seeks first to account for the collective variance of all the species used as input, and so typically prior to rotation the first component, explaining a maximum of the total variance tends to be “crustal” even though these elements together typically account for only a small fraction of the fine mass.

Subsequent rotational schemes Varimax, Procrustes, etc. These models also require can only find sources of fixed, unique chemical composition and variable, unique contribution. Soil itself has a highly variable composition but tends to be more alkaline in the West than in the East, very alkaline in areas with calcarious bedrock, and different yet again in the Sahara Dust and Asian Dust which often result in the highest soil contributions in the Eastern US and West coasts respectively.

These more distant dust events also tend to have much smaller particle size distributions than “local dust” emissions, as the larger particles are more readily removed during transport. Conversely, many other sources also contain “crustal impurities” coal fly ash for example , and so when one obtains a “pure crustal source” from a factor analysis it’s not entirely clear what that source actually represents.

While high dust concentrations that also build up under stagnation conditions from road dust emissions or dust from more distant origins will tend to B-ll get mixed into other modeled sources. Quite possibly the consistent finding of negative health associations with dust just reflects windy days when folks stay indoors and the air is otherwise at its cleanest.

For example: I think the not unreasonable use of wind speed as a dust surrogate is telling, as dust emissions especially the maximum concentrations are uniquely associated with high wind speeds – which in turn will tend to minimize concentrations of all other fine particle and gaseous components – assuring minimal chemical reactions between crustal particles and other species.

High concentrations of crustal particles and chemically associated contaminants on the surface of coarse particles from MV, SO2 or smelting activities would also reach high concentrations as would many other gaseous and PM pollutants on local stagnation days with low mixing heights – but would not be considered with this “wind speed” surrogate nor would dust of distant origin.

Potentially outdoor activities are curtailed on very windy, “local” dusty days, windows are closed, inhalation efficiency of coarse particles likely decreases with wind speed, and the spatial representativeness of “central site monitors” diminishes. Conversely, the lengthy Section 8.

Yet on p. Smith et al. It is also specifically emphasized that the authors “observed that the implication that crustal, rather than anthropogenic elements, for the observed relationship with mortality was counterintuitive. Emphasizing the potential importance of coarse biological content is reasonable, but on p.

For example, the geographically-focused incidence of “Valley Fever” specifically caused by caused by the fungus Coccidioides sp. In such situations, the relationship between hospital admissions and PM10 may be an indicator of response to coarse thoracic particles from wood burning.

I also question whether the NW has a high coarse: I’m getting picky here, but again it looks like trying too hard to show “it must be anything but crustal emissions” Becker S, Soukup J. Coarse PM 2. J Toxicol Environ Health A. Response of human alveolar macrophages to ultrafme, fine, and coarse urban air pollution particles. Exp Lung Res. Involvement of microbial components and toll-like receptors 2 and 4 in cytokine responses to air pollution particles.

Soukup JM, Becker S. Human alveolar macrophage responses to air pollution particulates are associated with insoluble components of coarse material, including paniculate endotoxin. Toxicol Appl Pharmacol. Coarse and fine particles and daily mortality in the Coachella Valley, California: J Expo Anal Environ Epidemiol. Air pollution and daily mortality in the Coachella Valley, California: Environ Res.

Effects of ambient air pollution on nonelderly asthma hospital admissions in Seattle, Washington, Effect of the fine fraction of particulate matter versus the coarse mass and other pollutants on daily mortality in Santiago, Chile. J Air Waste Manag Assoc. Burnett et al. The influence of ambient coarse particulate matter on asthma hospitalization in children: Environ Health Perspect.

Sheppard L et al. Inflammatory mediators induced by coarse PM2. Ambient fine and coarse particle suppression of alveolar macrophage functions. Toxicol Lett. B Monn C, Becker S. Cytotoxicity and induction of proinflammatory cytokines from human monocytes exposed to fine PM2. Toxicol Appl Pharmacol ; Inflammatory effects of coarse and fine particulate matter in relation to chemical and biological constituents.

Temporal variation of hydroxyl radical generation and 8- hydroxy-2′-deoxyguanosine formation by coarse and fine particulate matter. Occup Environ Med. Particle-induced oxidative damage is ameliorated by pulmonary antioxidants. Free Rad Biol Med. Associations between air pollution and mortality in Phoenix, Environ Health Perspect ; Airborne coarse particles and mortality.

Inhal Toxicol ; 12 supplement l: Gift, J. Exposure- Response Assessment,” J. Analysis Environ. Wright, G. New York: International Agency for Research on Cancer: Geneva, Switzerland: November Buchwaldt, L. Windborne dispersal of Colletotrichum truncatum and survival in infested lentil debris. Ecology and Epidemiology Gloster, J. Sellers, and A. Long distance transport of foot-and-mouth disease virus over B the sea.

The Veterinary Record Jan. Griffin, D. Garrison, etal. African desert dust in the Caribbean atmosphere: Microbiology and public health. Aerobiologia 17 June Kellogg, and E. Dust in the wind: Long range transport of dust in the atmosphere and its implications for global public and ecosystem health. Global Change and Human Health September. O’Hara, S. Exposure to airborne dust contaminated with pesticide in the Aral Sea region. Lancet Feb. Prospero, J.

Long-term measurements of the transport of African mineral dust to the southeastern United States: Implications for regional air quality. Journal of Geophysical Research July The Initial Pulmonary Infection and Beyond. Seminars in Respiratory and Critical Care Medicine ; Galgiani JN. Current Clinical Topics in Infectious Diseases. Clinical Infectious Diseases ; Western Journal of Medicine ; Rakel RE, ed. Conn’s Current Therapy.

WB Saunders Co. Coccidioidomycosis in human immunodeficiency virus-infected patients. Journal of Infectious Diseases ;

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