Border Searches of Electronic Devices

In fiscal year 2018, U.S. Customs and Border Protection (“CBP”) searched 33,295 electronic devices at the border without first needing a warrant. In fiscal year 2015, only about 8,500 electronic devices were searched at the border; in fiscal year 2016 that number rose to about 19,000; in fiscal year 2017 the number of devices searched increased again to over 30,000. The continued nontrivial increases in the number of electronic devices searched at the border, amounting to over 33,000 in fiscal year 2018, reveal that border searches of electronic devices are occurring more and more frequently with each passing year. The government is able to conduct these searches without obtaining warrants because, while the Fourth Amendment protects individuals’ “persons, houses, papers, and effects” from unreasonable searches and seizures, searches at the border have been exempt from Fourth Amendment protection. This exception is known doctrinally as the border search exception. The border search exception originally was designed to allow border agents to search travelers’ luggage for contraband and other harmful materials. However, with the progress of technology, the border search exception is now being exploited by border agents to conduct forensic searches of travelers’ electronic devices. Forensic searches are essentially “computer strip search[es],” wherein the government uses forensic software to access all active or readable files on the device, as well as password-protected data, hidden or encrypted data, deleted files, metadata, and unallocated file space. The smartphones, laptops, and tablets which accompany travelers to the border provide border agents unfettered access to vast quantities of personal information, without the protection of the Fourth Amendment. This Note first provides background on the Fourth Amendment and the border search exception. Second, this Note discusses the landmark cases Riley v. California and Carpenter v. United States to demonstrate how the Supreme Court has addressed digital data in the Fourth Amendment context. Third, this Note examines the circuit split between the Eleventh Circuit and the Fourth and Ninth Circuits regarding how electronic devices have been treated at the border. This Note then assesses the arguments for and against warrantless forensic searches of electronic devices at the border, and resolves the legal conflict in favor of greater privacy protections in electronic devices at the border

Monitoring kidney optical properties during cold storage preservation with spatial frequency domain imaging.

Transplantation of kidneys results in delayed graft function in as many as 40% of cases. During the organ transplantation process, donor kidneys undergo a period of cold ischemic time (CIT), where the organ is preserved with a cold storage solution to maintain tissue viability. Some complications observed after grafting may be due to damage sustained to the kidney during CIT. However, the effects due to this damage are not apparent until well after transplant surgery has concluded. To this end, we have used spatial frequency domain imaging (SFDI) to measure spatially resolved optical properties of porcine kidneys over the course of 80-h CIT. During this time, we observed an increase in both reduced scattering (μs&') and absorption (μa) coefficients. The measured scattering b parameter increased until 24 h of CIT, then returned toward baseline during the remaining duration of the imaging sequence. These results show that the optical properties of kidney tissue change with increasing CIT and suggest that continued investigation into the application of SFDI to kidneys under CIT may lead to the development of a noninvasive method for assessing graft viability

Corticospinal excitability of trunk muscles in anticipatory postural adjustments.

Objective: To investigate corticospinal excitability of trunk muscles during anticipatory postural adjustments (APAs) prior to a fast shoulder flexion task in an elderly and young cohort. Methods: Twenty young healthy (20.3 ± 1.4 years) and 20 elderly adults (75.5 ± 4.8 years) completed questionnaires, balance and neurophysiological assessments. Participants underwent balance tasks on a force plate, which recorded their centre of pressure displacement. A recognition reaction time (RRT) paradigm was used where participants responded to a visual stimulus by flexing their shoulders bilaterally as fast as they could. Activity of bilateral anterior deltoid (AD) and erector spinae (ES) muscles were recorded using electromyography (EMG). Onset of AD and ES EMG was measured to represent RRT and APAs, respectively. Transcranial magnetic stimulation (TMS) was used to assess corticospinal excitability of the ES prior to the shoulder flexion task. Maximal voluntary contraction (MVC) of the ES was measured. Results: The amplitude of ES motor evoked potentials (MEPs) was greater at 40ms than 50ms, and at 30ms than 40ms, prior to the onset of AD EMG in both cohorts. ES MEP amplitude at 40ms prior to the onset of AD EMG correlated with the onset of ES EMG in the elderly cohort only. A higher percentage of elderly individuals had delayed APA (75%) compared to young. Elderly participants showed greater postural sway during balance tasks. Conclusions: Our findings outline the corticospinal excitability profile of trunk muscles during APAs in older adults, and suggest older adults have greater motor cortical involvement in APA function

Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data

For the long term control of an infectious disease such as COVID-19, it is crucial to identify the most likely individuals to become infected and the role that differences in demographic characteristics play in the observed patterns of infection. As high-volume surveillance winds down, testing data from earlier periods are invaluable for studying risk factors for infection in detail. Observed changes in time during these periods may then inform how stable thepattern will be in the long term.To this end we analyse the distribution of cases of COVID-19 across Scotland in 2021, where the location (census areas of order 500–1,000 residents) and reporting date of cases are known. We consider over 450,000 individually recorded cases, in two infection waves triggered by different lineages: B.1.1.529 (“Omicron”) and B.1.617.2 (“Delta”). We use random forests, informed by measures of geography, demography, testing and vaccination. We show that the distributions are only adequately explained when considering multiple explanatory variables, implying that case heterogeneity arose from a combination of individual behaviour, immunity, and testing frequency.Despite differences in virus lineage, time of year, and interventions in place, we find the risk factors remained broadly consistent between the two waves. Many of the observed smaller differences could be reasonably explained by changes in control measures

Burn wound classification model using spatial frequency-domain imaging and machine learning.

Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have been used to examine tissue properties to infer burn severity. Spatial frequency-domain imaging (SFDI) has also been used to characterize burns based on the relationships between histologic observations and changes in tissue properties. Recently, machine learning has been used to classify burns by combining optical features from multispectral or hyperspectral imaging. Rather than employ models of light propagation to deduce tissue optical properties, we investigated the feasibility of using SFDI reflectance data at multiple spatial frequencies, with a support vector machine (SVM) classifier, to predict severity in a porcine model of graded burns. Calibrated reflectance images were collected using SFDI at eight wavelengths (471 to 851 nm) and five spatial frequencies (0 to 0.2  mm  -  1). Three models were built from subsets of this initial dataset. The first subset included data taken at all wavelengths with the planar (0  mm  -  1) spatial frequency, the second comprised data at all wavelengths and spatial frequencies, and the third used all collected data at values relative to unburned tissue. These data subsets were used to train and test cubic SVM models, and compared against burn status 28 days after injury. Model accuracy was established through leave-one-out cross-validation testing. The model based on images obtained at all wavelengths and spatial frequencies predicted burn severity at 24 h with 92.5% accuracy. The model composed of all values relative to unburned skin was 94.4% accurate. By comparison, the model that employed only planar illumination was 88.8% accurate. This investigation suggests that the combination of SFDI with machine learning has potential for accurately predicting burn severity

Experimental hut and bioassay evaluation of the residual activity of a polymer-enhanced suspension concentrate (SC-PE) formulation of deltamethrin for IRS use in the control of Anopheles arabiensis.

BACKGROUND: The Stockholm Convention on Persistent Organic Pollutants (POPs) came into effect in 2004; the use of DDT for malaria control has been allowed to continue under exemption since then due to a perceived absence of equally effective and efficient alternatives. Alternative classes of insecticide for indoor residual spraying (IRS) have a relatively short residual duration of action (2-6 months according to WHO). In areas of year-round transmission multiple spray cycles are required, resulting in significantly higher costs for malaria control programs and user fatigue. This study evaluated performance of a new formulation of deltamethrin (pyrethroid) with polymer (SC-PE) to prolong the effective residual action to >6 months. METHODS: Deltamethrin SC-PE was evaluated alongside an existing water dispersible granule (WG) formulation and DDT water dispersible powder (WP) in laboratory and hut bioassays on mud, concrete, palm thatch and plywood substrates. An experimental hut trial was conducted in Lower Moshi Rice Irrigation Zone, Tanzania from 2008-2009 against wild, free-flying, pyrethroid susceptible An. arabiensis. Performance was measured in terms of insecticide-induced mortality, and blood-feeding inhibition. Bioassays were carried out monthly on sprayed substrates to assess residual activity. RESULTS: Bioassays in simple huts (designed for bioassay testing only) and experimental huts (designed for testing free flying mosquitoes) showed evidence that SC-PE improved longevity on mud and concrete over the WG formulation. Both deltamethrin SC-PE and WG outperformed DDT in bioassays on all substrates tested in the laboratory and simple huts. In experimental hut trials SC-PE, WG and DDT produced high levels of An. arabiensis mortality and the treatments were equivalent over nine months' duration. Marked seasonal changes in mortality were recorded for DDT and deltamethrin treatments, and may have been partly influenced by outdoor temperature affecting indoor resting duration of mosquitoes on sprayed surfaces, although no clear correlation was demonstrated. CONCLUSIONS: There is a limited range of alternative insecticides for IRS, and deltamethrin SC-PE is likely to have an important role as part of a rotation strategy with one or more different insecticide classes rotated annually, particularly in areas that currently have low levels of pyrethroid resistance or low LLIN coverage and year-round malaria transmission

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature

Non-adjacent dependency learning in infancy, and its link to language development.

To acquire language, infants must learn how to identify words and linguistic structure in speech. Statistical learning has been suggested to assist both of these tasks. However, infants’ capacity to use statistics to discover words and structure together remains unclear. Further, it is not yet known how infants' statistical learning ability relates to their language development. We trained 17-month-old infants on an artificial language comprising non- adjacent dependencies, and examined their looking times on tasks assessing sensitivity to words and structure using an eye-tracked head-turn-preference paradigm. We measured infants’ vocabulary size using a Communicative Development Inventory (CDI) concurrently and at 19, 21, 24, 25, 27, and 30 months to relate performance to language development. Infants could segment the words from speech, demonstrated by a significant difference in looking times to words versus part-words. Infants’ segmentation performance was significantly related to their vocabulary size (receptive and expressive) both currently, and over time (receptive until 24 months, expressive until 30 months), but was not related to the rate of vocabulary growth. The data also suggest infants may have developed sensitivity to generalised structure, indicating similar statistical learning mechanisms may contribute to the discovery of words and structure in speech, but this was not related to vocabulary size