Metaphyseal trauma of the lower extremities in major orthopedic surgery as an independent risk factor for deep vein thrombosis.

PURPOSE: Major orthopedic surgeries of the lower extremities, which heavily injure the metaphyseal region, are strongly associated with the risk of developing deep vein thrombosis (DVT). This study aims to investigate the role of metaphyseal trauma as an independent risk factor for DVT. METHODS: Patients undergoing major orthopedic surgery of the hip and knee had their existing DVT risk factors recorded. Metaphyseal trauma was defined by the extent of bone injury during these surgeries. The samples were categorized into three surgery groups: total arthroplasty group (TA), hemiarthroplasty group (HA), and the open reduction internal fixation group (ORIF). Logistic regression test between significant existing risk factors and surgery groups determines the independent association between risk factors and DVT. RESULT: The study found a 24.8% incidence of asymptomatic DVT in patients undergoing major orthopedic surgeries, with the highest prevalence (37.2%) in TA, which had the largest extent of metaphyseal trauma and the least existing DVT risk factors. TA showed 6.2 OR and 95% CI (p = 0.036) compared to the other existing risk factor in relation to DVT incidence. CONCLUSION: Metaphyseal bone trauma in the hip and knee major orthopedic surgery is an independent risk factor for deep vein thrombosis.

Inductive detection of influence operations via graph learning.

Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies may enable novel operations that evade detection and influence public discourse on social media with greater scale, reach, and specificity. New methods of detection with inductive learning capacity will be needed to identify novel operations before they indelibly alter public opinion and events. To this end, we develop an inductive learning framework that: (1) determines content- and graph-based indicators that are not specific to any operation; (2) uses graph learning to encode abstract signatures of coordinated manipulation; and (3) evaluates generalization capacity by training and testing models across operations originating from Russia, China, and Iran. We find that this framework enables strong cross-operation generalization while also revealing salient indicators-illustrating a generic approach which directly complements transductive methodologies, thereby enhancing detection coverage.

The online competition between pro- and anti-vaccination views.

Distrust in scientific expertise1-14 is dangerous. Opposition to vaccination with a future vaccine against SARS-CoV-2, the causal agent of COVID-19, for example, could amplify outbreaks2-4, as happened for measles in 20195,6. Homemade remedies7,8 and falsehoods are being shared widely on the Internet, as well as dismissals of expert advice9-11. There is a lack of understanding about how this distrust evolves at the system level13,14. Here we provide a map of the contention surrounding vaccines that has emerged from the global pool of around three billion Facebook users. Its core reveals a multi-sided landscape of unprecedented intricacy that involves nearly 100 million individuals partitioned into highly dynamic, interconnected clusters across cities, countries, continents and languages. Although smaller in overall size, anti-vaccination clusters manage to become highly entangled with undecided clusters in the main online network, whereas pro-vaccination clusters are more peripheral. Our theoretical framework reproduces the recent explosive growth in anti-vaccination views, and predicts that these views will dominate in a decade. Insights provided by this framework can inform new policies and approaches to interrupt this shift to negative views. Our results challenge the conventional thinking about undecided individuals in issues of contention surrounding health, shed light on other issues of contention such as climate change11, and highlight the key role of network cluster dynamics in multi-species ecologies15.

Quantifying COVID-19 Content in the Online Health Opinion War Using Machine Learning.

A huge amount of potentially dangerous COVID-19 misinformation is appearing online. Here we use machine learning to quantify COVID-19 content among online opponents of establishment health guidance, in particular vaccinations ("anti-vax"). We find that the anti-vax community is developing a less focused debate around COVID-19 than its counterpart, the pro-vaccination ("pro-vax") community. However, the anti-vax community exhibits a broader range of "flavors" of COVID-19 topics, and hence can appeal to a broader cross-section of individuals seeking COVID-19 guidance online, e.g. individuals wary of a mandatory fast-tracked COVID-19 vaccine or those seeking alternative remedies. Hence the anti-vax community looks better positioned to attract fresh support going forward than the pro-vax community. This is concerning since a widespread lack of adoption of a COVID-19 vaccine will mean the world falls short of providing herd immunity, leaving countries open to future COVID-19 resurgences. We provide a mechanistic model that interprets these results and could help in assessing the likely efficacy of intervention strategies. Our approach is scalable and hence tackles the urgent problem facing social media platforms of having to analyze huge volumes of online health misinformation and disinformation.

Thermoluminescence measurement technique using millisecond temperature pulses.

A measurement technique, pulsed thermoluminescence, is described which uses short thermal pulses to excite trapped carriers leading to radiative recombination. The pulses are obtained using microstructures with approximately 500 micros thermal time constants. The technique has many of the advantages of pulsed optically stimulated luminescence without the need for optical sources and filters to isolate the luminescent signal. Charge carrier traps in alpha-Al(2)O(3):C particles on microheaters were filled using 205 nm light. Temperature pulses of 10 and 50 ms were applied to the heaters and compared with a standard thermoluminescence curve taken at a ramp rate of 5 K s(-1). This produced curves of intensity verses temperature similar to standard thermoluminescence except shifted to higher temperatures. The luminescence of single particles was read multiple times with negligible loss of population. The lower limit of the duration of useful pulses appears to be limited by particle size and thermal contact between the particle and heater.

Optical coatings in microscale channels by atomic layer deposition.

High-aspect-ratio channels may be coated using atomic layer deposition (ALD) due to the unique self-limiting nature of the process, and this has been often demonstrated using deep reactive-ion etched trenches in silicon. However, for optical and microfluidic applications, many channels are centimeters deep with diameters of tens to hundreds of micrometers, and the relatively large area exposes more difficult problems of temperature and gas flow uniformity. To quantify the uniformity of optical coatings deposited by ALD under those conditions, an air wedge has been created between two square wafers of silicon approximately 7 cm on a side, with the air gap varying linearly from 0-1560 microm. ALD aluminum oxide uniformity is astounding, while hafnium oxide shows a need for process optimization, but still exceeds the capability observed in other deposition techniques. A six-layer Fabry-Perot optical cavity with fixed 500 nm resonance was deposited inside a wedge, and the measured resonant wavelength closely matched predictions, except at the deepest regions of the wedge.

Infrared absorption signature on laser-damaged optical thin films.

Optical coating degradation under laser irradiation can take several forms. Perhaps the most common that is not due to particulates is thermal breakdown, caused by heating of the coating to a catastrophic failure induced by local melting, delamination, evaporation, or some other change. We demonstrate that micromachined dielectric membranes show strong differences in their hydroxyl signatures as measured by Fourier-transform IR spectroscopy. The changes correspond to regions of high fluence (3200 J/cm2) from a Nd:YAG laser. It is found that the absorption peaks associated with OH decrease after laser treatment, indicating a reduction in the number of film hydroxyl groups.

Control of thermal deformation in dielectric mirrors using mechanical design and atomic layer deposition.

A mechanical design technique for optical coatings that simultaneously controls thermal deformation and optical reflectivity is reported. The method requires measurement of the refractive index and thermal stress of single films prior to the design. Atomic layer deposition was used for deposition because of the high repeatability of the film constants. An Al2O3/HfO2 distributed Bragg reflector was deposited with a predicted peak reflectivity of 87.9% at 542.4 nm and predicted edge deformation of -360 nm/K on a 10 cm silicon substrate. The measured peak reflectivity was 85.7% at 541.7 nm with an edge deformation of -346 nm/K.

Encapsulation of low-refractive-index SiO(2) nanorods by Al(2)O(3) with atomic layer deposition.

Thin films composed of SiO(2) nanorods or nanoporous SiO(2) (np- SiO(2)) are attractive for use as a low refractive index material in various types of optical coatings. However, the material properties of these films are unstable because of the high porosity of the films. This is particularly apparent in dry versus humid atmospheres where both the refractive index and coefficient of thermal expansion (CTE) vary dramatically. In this article, we demonstrate that np-SiO(2) can be encapsulated by depositing Al(2)O(3) with Atomic Layer Deposition (ALD), stabilizing these properties. In addition, this encapsulation ability is demonstrated successfully in a 4-pair distributed Bragg reflector (DBR) design. It is hoped that this technique will be useful in patterning specific regions of a film for optical and mechanical stability while other portions are ambient-interactive for sensing.