Memory retrieval effects as a function of differences in phenomenal experience.

Conscious experience and perception are restricted to a single perspective. Although evidence to suggest differences in phenomenal experience can produce observable differences in behavior, it is not well understood how these differences might influence memory. We used fMRI to scan n = 49 participants while they encoded and performed a recognition memory test for faces and words. We calculated a cognitive bias score reflecting individual participants' propensity toward either Visual Imagery or Internal Verbalization based on their responses to the Internal Representations Questionnaire (IRQ). Neither visual imagery nor internal verbalization scores were significantly correlated with memory performance. In the fMRI data, there were typical patterns of activation differences between words and faces during both encoding and retrieval. There was no effect of internal representation bias on fMRI activation during encoding. At retrieval, however, a bias toward visualization was positively correlated with memory-related activation for both words and faces in inferior occipital gyri. Further, there was a crossover interaction in a network of brain regions such that visualization bias was associated with greater activation for words and verbalization bias was associated with greater activation for faces, consistent with increased effort for non-preferred stimulus retrieval. These findings suggest that individual differences in cognitive representations affect neural activation across different types of stimuli, potentially affecting memory retrieval performance.

Large-Format Additive Manufacturing and Machining Using High-Melt-Temperature Polymers. Part I: Real-Time Particulate and Gas-Phase Emissions.

The literature on emissions during material extrusion additive manufacturing with 3-D printers is expanding; however, there is a paucity of data for large-format additive manufacturing (LFAM) machines that can extrude high-melt-temperature polymers. Emissions from two LFAM machines were monitored during extrusion of six polymers: acrylonitrile butadiene styrene (ABS), polycarbonate (PC), high-melt-temperature polysulfone (PSU), poly(ether sulfone) (PESU), polyphenylene sulfide (PPS), and Ultem (poly(ether imide)). Particle number, total volatile organic compound (TVOC), carbon monoxide (CO), and carbon dioxide (CO2) concentrations were monitored in real-time. Particle emission rate values (no./min) were as follows: ABS (1.7 × 1011 to 7.7 × 1013), PC (5.2 × 1011 to 3.6 × 1013), Ultem (5.7 × 1012 to 3.1 × 1013), PPS (4.6 × 1011 to 6.2 × 1012), PSU (1.5 × 1012 to 3.4 × 1013), and PESU (2.0 to 5.0 × 1013). For print jobs where the mass of extruded polymer was known, particle yield values (g-1 extruded) were as follows: ABS (4.5 × 108 to 2.9 × 1011), PC (1.0 × 109 to 1.7 × 1011), PSU (5.1 × 109 to 1.2 × 1011), and PESU (0.8 × 1011 to 1.7 × 1011). TVOC emission yields ranged from 0.005 mg/g extruded (PESU) to 0.7 mg/g extruded (ABS). The use of wall-mounted exhaust ventilation fans was insufficient to completely remove airborne particulate and TVOC from the print room. Real-time CO monitoring was not a useful marker of particulate and TVOC emission profiles for Ultem, PPS, or PSU. Average CO2 and particle concentrations were moderately correlated (r s = 0.76) for PC polymer. Extrusion of ABS, PC, and four high-melt-temperature polymers by LFAM machines released particulate and TVOC at levels that could warrant consideration of engineering controls. LFAM particle emission yields for some polymers were similar to those of common desktop-scale 3-D printers.

Large-Format Additive Manufacturing and Machining Using High-Melt-Temperature Polymers. Part II: Characterization of Particles and Gases.

Extrusion of high-melt-temperature polymers on large-format additive manufacturing (LFAM) machines releases particles and gases, though there is no data describing their physical and chemical characteristics. Emissions from two LFAM machines were monitored during extrusion of acrylonitrile butadiene styrene (ABS) and polycarbonate (PC) polymers as well as high-melt-temperature Ultem (poly(ether imide)), polysulfone (PSU), poly(ether sulfone) (PESU), and polyphenylene sulfide (PPS) polymers. Filter samples of particles were collected for quantification of elements and bisphenol A and S (BPA, BPS) and visualization of morphology. Individual gases were quantified on substance-specific media. Aerosol sampling demonstrated that concentrations of elements were generally low for all polymers, with a maximum of 1.6 mg/m3 for iron during extrusion of Ultem. BPA, an endocrine disruptor, was released into air during extrusion of PC (range: 0.4 ± 0.1 to 21.3 ± 5.3 µg/m3). BPA and BPS (also an endocrine disruptor) were released into air during extrusion of PESU (BPA, 2.0-8.7 µg/m3; BPS, 0.03-0.07 µg/m3). Work surfaces and printed parts were contaminated with BPA (<8-587 ng/100 cm2) and BPS (<0.22-2.5 ng/100 cm2). Gas-phase sampling quantified low levels of respiratory irritants (phenol, SO2, toluene, xylenes), possible or known asthmagens (caprolactam, methyl methacrylate, 4-oxopentanal, styrene), and possible occupational carcinogens (benzene, formaldehyde, acetaldehyde) in air. Characteristics of particles and gases released by high-melt-temperature polymers during LFAM varied, which indicated the need for polymer-specific exposure and risk assessments. The presence of BPA and BPS on surfaces revealed a previously unrecognized source of dermal exposure for additive manufacturing workers using PC and PESU polymers.

An integrative literature review of barriers and facilitators to cervical cancer screening among refugee women in the United States.

Refugee women experience disproportionally high cervical cancer-related mortality. In this integrative review, we identify and discuss factors related to cervical cancer screening among refugee women in the US according to the Social Ecological Model. Two qualitative and three quantitative studies met inclusion criteria. Individual-level factors include English-language ability, availability, and individual knowledge, attitudes, and beliefs. Interpersonal-level factors include interactions with family/friends, provider, and community health worker. Community-, organization-, and policy-level factors include sociocultural values, transportation, ability to navigate the healthcare system, and health insurance. We discuss findings in the context of related reviews and applicability to other global settings.