Shelton Davis and Applied Anthropology

This essay celebrates Shelton Davis’ rich and diverse career as an advocate of indigenous peoples’ rights and a major critic of mainline development models being implemented in the Third World. As an applied anthropologist, Davis rejected any division between knowledge and action in relation to indigenous and other populations directly affected by large-scale development. Through his writing and actions, he showed it was possible to maintain both objectivity and advocacy in dramatic situations such as those of the Guatemalan Mayan peoples. His contributions to community service, in founding at least two international NGOs, and his work at the World Bank, where he showed brilliant creativity, marked his unique, pioneering work and lasting contributions. Este ensaio destaca a carreira rica e diversa do Shelton Davis enquanto aliado dos povos indígenas nas suas lutas por seus direitos. Davis demostrou, através de suas escritas e ativismo, que era perfeitamente possível manter tanto a objetividade quanto o ativismo politico. As suas contribuições em termos de serviços comunitários, criando pelo menos duas organizações não-governamentais, e seu trabalho com o Banco Mundial, marcaram a sua carreira pioneira e única

The Work of Expert Testimony: Central Americans, Human Rights Defenders, and Immigration Courts

Anthropologists have worked in legal arenas as experts on civil, criminal, and asylum cases throughout the history of the discipline. Today expert witnesses give opinions on the conditions of countries where immigrants flee, and that work includes ethnographic interviewing, research into the causes of political and social violence, and appearing in court through written affidavits and personal testimony. Expert testimony today includes helping in the defense of people fleeing intimate partner violence, persecution based on sexual orientation, threats and violence by gangs, and those whose political opinions put them at risk. Immigrants in the United States face institutional culture shock, structural violence, and criminalization of their lives. Case studies of immigration, civil, and criminal cases illustrate how theory and practice intersect in the harsh light of court cases

Non-stochastic lattice structures for novel filter applications fabricated via additive manufacturing

Non-stochastic lattice structures are widely used in a variety of applications such as biomedical implants and heat exchangers. However, the utilisation of these structures for filtration applications is rather new. Additive manufacturing techniques such as selective laser melting allows lattice structures to be bespoke depending on the type of filter and its intended function. This study considers the flow characteristics and structural strength of a disc filter with a layer of repeated 1.8 mm lattice unit cell as the filter mesh. Computational fluid dynamics simulation is used to analyse the pressure and flow velocity across the filter, while finite element analysis is utilised to analyse the structural characteristics of the lattice mesh under fluid load. The results show a minimal decrease in pressure and small increases in velocity, with the mesh capable of withstanding higher loads. The ultimate failure load of the structure is also determined. These findings indicate that more layers of lattice structures could be used as filter mesh and the flexibility of AM allows the filter properties to be tailored as required for a given application

The Design and Application of a Scale to Measure Attitudes of Secondary School Administrators Toward Vocational Education

Statement of the Problem: The problem of this study was to design a valid and reliable instrument to measure the attitudes of secondary school administrators toward vocational education. Procedure: The parameters of the attitude to be measured were identified and defined. Based on these definitions, a 96-task universe of content was compiled and evaluated by a jury of vocational administrators and judged complete and relevant to the role of a vocational administrator. Fifty tasks were randomly selected from the universe and related attitude statements were written. In addition to the 50 statements, 7 selected demographic questions were included in the original instrument. A Likert summated rating scale was chosen as the method of measurement. The instrument was pilot tested, revised, and field tested on a population of 200 subjects. Through item analysis, the final instrument was reduced to the 24 highest discriminating attitude statements and 3 demographic questions. Analysis of Data and Findings: An estimate of scale reliability with a coefficient of .88 was computed with the K-R 20 formula. One claim of content validity was made as a result of the completeness of the universe of content. One claim of construct validity was made based on the significant difference in scores between the known groups. Conclusions: Based on the findings in this study, several conclusions were made: 1) The scale items are unidimensional. 2) The scale has a high level of internal consistency. 3) The scale appears to be significantly reliable. 4) The scale has content validity. 5) The scale has construct validity. 6) The demographic questions provided no significant correlational data. 7) The 24-item scale designed in this study appears to be able to measure the attitudes of secondary school administrators toward vocational education. Recommendations: From the general conclusions presented, recommendations related to the scale designed in this study were: 1) Research should be conducted in an effort to replicate the statistical estimates of reliability and validity. 2) Research should be conducted utilizing this instrument to measure the attitudes of secondary school administrators. 3) Research should be conducted to re-evaluate the validity and reliability of this scale incorporating alternate statistical procedures. 4) Research should be conducted to determine if selected demographics beyond those used in this study influence attitude scores

Techniques utilized in the simulated altitude testing of a 2D-CD vectoring and reversing nozzle

Simulated altitude testing of a two-dimensional, convergent-divergent, thrust vectoring and reversing exhaust nozzle was accomplished. An important objective of this test was to develop test hardware and techniques to properly operate a vectoring and reversing nozzle within the confines of an altitude test facility. This report presents detailed information on the major test support systems utilized, the operational performance of the systems and the problems encountered, and test equipment improvements recommended for future tests. The most challenging support systems included the multi-axis thrust measurement system, vectored and reverse exhaust gas collection systems, and infrared temperature measurement systems used to evaluate and monitor the nozzle. The feasibility of testing a vectoring and reversing nozzle of this type in an altitude chamber was successfully demonstrated. Supporting systems performed as required. During reverser operation, engine exhaust gases were successfully captured and turned downstream. However, a small amount of exhaust gas spilled out the collector ducts' inlet openings when the reverser was opened more than 60 percent. The spillage did not affect engine or nozzle performance. The three infrared systems which viewed the nozzle through the exhaust collection system worked remarkably well considering the harsh environment

EVALUATING ARTIFICIAL INTELLIGENCE METHODS FOR USE IN KILL CHAIN FUNCTIONS

Current naval operations require sailors to make time-critical and high-stakes decisions based on uncertain situational knowledge in dynamic operational environments. Recent tragic events have resulted in unnecessary casualties, and they represent the decision complexity involved in naval operations and specifically highlight challenges within the OODA loop (Observe, Orient, Decide, and Assess). Kill chain decisions involving the use of weapon systems are a particularly stressing category within the OODA loop—with unexpected threats that are difficult to identify with certainty, shortened decision reaction times, and lethal consequences. An effective kill chain requires the proper setup and employment of shipboard sensors; the identification and classification of unknown contacts; the analysis of contact intentions based on kinematics and intelligence; an awareness of the environment; and decision analysis and resource selection. This project explored the use of automation and artificial intelligence (AI) to improve naval kill chain decisions. The team studied naval kill chain functions and developed specific evaluation criteria for each function for determining the efficacy of specific AI methods. The team identified and studied AI methods and applied the evaluation criteria to map specific AI methods to specific kill chain functions.Civilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCaptain, United States Marine CorpsCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Understanding powder degradation in metal additive manufacturing to allow the upcycling of recycled powders

To ensure the financial viability of powder-based additive manufacturing technologies, the recycling of powders is common practice. This paper shows the lifecycle of metal powder in additive manufacturing, investigating powder manufacture, powder usage, mechanisms of powder degradation and the usage of end-of-life powder. Degradation of powders resulting from repeated reuses was found to be a widespread problem; components produced from heavily reused powders are typically of a lower quality, eventually rendering the powder unusable in additive manufacturing. Powder degradation was found to be dependent on many variables, preventing the identification of a definitive end-of-life point for powders. The most accurate method of determining powder quality was found to be the production and analysis of components using these powders. Uses for degraded powder had not been previously identified in literature, warranting the investigation of potential solutions to prevent powder waste. Amongst other waste-reducing solutions, plasma spheroidisation was identified as a promising method to avoid powder disposal for approximately 12.5% of produced powders, creating particles similar to virgin powder from end-of-life powder. Returning end-of-life powders to the supplier for upcycling may be the only financially viable solution to reduce waste within the industry. The compilation of research within this paper aims to enable users of additive manufacturing to conduct further research and development into powder upcycling

Permutation Equivariant Neural Functionals

This work studies the design of neural networks that can process the weights or gradients of other neural networks, which we refer to as neural functional networks (NFNs). Despite a wide range of potential applications, including learned optimization, processing implicit neural representations, network editing, and policy evaluation, there are few unifying principles for designing effective architectures that process the weights of other networks. We approach the design of neural functionals through the lens of symmetry, in particular by focusing on the permutation symmetries that arise in the weights of deep feedforward networks because hidden layer neurons have no inherent order. We introduce a framework for building permutation equivariant neural functionals, whose architectures encode these symmetries as an inductive bias. The key building blocks of this framework are NF-Layers (neural functional layers) that we constrain to be permutation equivariant through an appropriate parameter sharing scheme. In our experiments, we find that permutation equivariant neural functionals are effective on a diverse set of tasks that require processing the weights of MLPs and CNNs, such as predicting classifier generalization, producing "winning ticket" sparsity masks for initializations, and classifying or editing implicit neural representations (INRs). In addition, we provide code for our models and experiments at https://github.com/AllanYangZhou/nfn.Comment: To appear in Neural Information Processing Systems (NeurIPS), 202

Neural Functional Transformers

The recent success of neural networks as implicit representation of data has driven growing interest in neural functionals: models that can process other neural networks as input by operating directly over their weight spaces. Nevertheless, constructing expressive and efficient neural functional architectures that can handle high-dimensional weight-space objects remains challenging. This paper uses the attention mechanism to define a novel set of permutation equivariant weight-space layers and composes them into deep equivariant models called neural functional Transformers (NFTs). NFTs respect weight-space permutation symmetries while incorporating the advantages of attention, which have exhibited remarkable success across multiple domains. In experiments processing the weights of feedforward MLPs and CNNs, we find that NFTs match or exceed the performance of prior weight-space methods. We also leverage NFTs to develop Inr2Array, a novel method for computing permutation invariant latent representations from the weights of implicit neural representations (INRs). Our proposed method improves INR classification accuracy by up to $+17\%$ over existing methods. We provide an implementation of our layers at https://github.com/AllanYangZhou/nfn