Single charge sensing and transport in double quantum dots fabricated from commercially grown Si/SiGe heterostructures

We perform quantum Hall measurements on three types of commercially available modulation doped Si/SiGe heterostructures to determine their suitability for depletion gate defined quantum dot devices. By adjusting the growth parameters, we are able to achieve electron gases with charge densities 1-3 X 10^{11}/cm^2 and mobilities in excess of 100,000 cm^2/Vs. Double quantum dot devices fabricated on these heterostructures show clear evidence of single charge transitions as measured in dc transport and charge sensing and exhibit electron temperatures of 100 mK in the single quantum dot regime.Comment: Related papers at http://pettagroup.princeton.ed

Charge Relaxation in a Single Electron Si/SiGe Double Quantum Dot

We measure the interdot charge relaxation time T_1 of a single electron trapped in an accumulation mode Si/SiGe double quantum dot. The energy level structure of the charge qubit is determined using photon assisted tunneling, which reveals the presence of a low lying excited state. We systematically measure T_1 as a function of detuning and interdot tunnel coupling and show that it is tunable over four orders of magnitude, with a maximum of 45 microseconds for our device configuration. Measured relaxation times are consistent with a phonon mediated energy relaxation process and indicate that low lying excited states may have important implications in the development of silicon spin qubits.Comment: Related papers at http://pettagroup.princeton.ed

Large-scale synchrony of gap dynamics and the distribution of understory tree species in maple-beech forests

Large-scale synchronous variations in community dynamics are well documented for a vast array of organisms, but are considerably less understood for forest trees. Because of temporal variations in canopy gap dynamics, forest communities—even old-growth ones—are never at equilibrium at the stand scale. This paucity of equilibrium may also be true at the regional scale. Our objectives were to determine (1) if nonequilibrium dynamics caused by temporal variations in the formation of canopy gaps are regionally synchronized, and (2) if spatiotemporal variations in canopy gap formation aVect the relative abundance of tree species in the understory. We examined these questions by analyzing variations in the suppression and release history of Acer saccharum Marsh. and Fagus grandifolia Ehrh. from 481 growth series of understory saplings taken from 34 mature stands. We observed that (1) the proportion of stems in release as a function of time exhibited a U-shaped pattern over the last 35 years, with the lowest levels occurring during 1975–1985, and that (2) the response to this in terms of species composition was that A. saccharum became more abundant at sites that had the highest proportion of stems in release during 1975–1985. We concluded that the understory dynamics, typically thought of as a stand-scale process, may be regionally synchronized

Can forest management based on natural disturbances maintain ecological resilience?

Given the increasingly global stresses on forests, many ecologists argue that managers must maintain ecological resilience: the capacity of ecosystems to absorb disturbances without undergoing fundamental change. In this review we ask: Can the emerging paradigm of natural-disturbance-based management (NDBM) maintain ecological resilience in managed forests? Applying resilience theory requires careful articulation of the ecosystem state under consideration, the disturbances and stresses that affect the persistence of possible alternative states, and the spatial and temporal scales of management relevance. Implementing NDBM while maintaining resilience means recognizing that (i) biodiversity is important for long-term ecosystem persistence, (ii) natural disturbances play a critical role as a generator of structural and compositional heterogeneity at multiple scales, and (iii) traditional management tends to produce forests more homogeneous than those disturbed naturally and increases the likelihood of unexpected catastrophic change by constraining variation of key environmental processes. NDBM may maintain resilience if silvicultural strategies retain the structures and processes that perpetuate desired states while reducing those that enhance resilience of undesirable states. Such strategies require an understanding of harvesting impacts on slow ecosystem processes, such as seed-bank or nutrient dynamics, which in the long term can lead to ecological surprises by altering the forest's capacity to reorganize after disturbance

Characteristics of undernourished older medical patients and the identification of predictors for undernutrition status

<p>Abstract</p> <p>Background</p> <p>Undernutrition among older people is a continuing source of concern, particularly among acutely hospitalized patients. The purpose of the current study is to compare malnourished elderly patients with those at nutritional risk and identify factors contributing to the variability between the groups.</p> <p>Methods</p> <p>The study was carried out at the Soroka University Medical Center in the south of Israel. From September 2003 through December 2004, all patients 65 years-of-age or older admitted to any of the internal medicine departments, were screened within 72 hours of admission to determine nutritional status using the short version of the Mini Nutritional Assessment (MNA-SF). Patients at nutritional risk were entered the study and were divided into malnourished or 'at risk' based on the full version of the MNA. Data regarding medical, nutritional, functional, and emotional status were obtained by trained interviewers.</p> <p>Results</p> <p>Two hundred fifty-nine elderly patients, 43.6% men, participated in the study; 18.5% were identified as malnourished and 81.5% were at risk for malnutrition according to the MNA. The malnourished group was less educated, had a higher depression score and lower cognitive and physical functioning. Higher prevalence of chewing problems, nausea, and vomiting was detected among malnourished patients. There was no difference between the groups in health status indicators except for subjective health evaluation which was poorer among the malnourished group. Lower dietary score indicating lower intake of vegetables fruits and fluid, poor appetite and difficulties in eating distinguished between malnourished and at-risk populations with the highest sensitivity and specificity as compare with the anthropometric, global, and self-assessment of nutritional status parts of the MNA. In a multivariate analysis, lower cognitive function, education <12 years and chewing problems were all risk factors for malnutrition.</p> <p>Conclusion</p> <p>Our study indicates that low food consumption as well as poor appetite and chewing problems are associated with the development of malnutrition. Given the critical importance of nutritional status in the hospitalized elderly, further intervention trials are required to determine the best intervention strategies to overcome these problems.</p

Fetal brain tissue annotation and segmentation challenge results.

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, gray matter, white matter, ventricles, cerebellum, brainstem, deep gray matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero

Psychosocial factors and cancer incidence (PSY-CA): Protocol for individual participant data meta-analyses

Objectives: Psychosocial factors have been hypothesized to increase the risk of cancer. This study aims (1) to test whether psychosocial factors (depression, anxiety, recent loss events, subjective social support, relationship status, general distress, and neuroticism) are associated with the incidence of any cancer (any, breast, lung, prostate, colorectal, smoking-related, and alcohol-related); (2) to test the interaction between psychosocial factors and factors related to cancer risk (smoking, alcohol use, weight, physical activity, sedentary behavior, sleep, age, sex, education, hormone replacement therapy, and menopausal status) with regard to the incidence of cancer; and (3) to test the mediating role of health behaviors (smoking, alcohol use, weight, physical activity, sedentary behavior, and sleep) in the relationship between psychosocial factors and the incidence of cancer. Methods: The psychosocial factors and cancer incidence (PSY-CA) consortium was established involving experts in the field of (psycho-)oncology, methodology, and epidemiology. Using data collected in 18 cohorts (N = 617,355), a preplanned two-stage individual participant data (IPD) meta-analysis is proposed. Standardized analyses will be conducted on harmonized datasets for each cohort (stage 1), and meta-analyses will be performed on the risk estimates (stage 2). Conclusion: PSY-CA aims to elucidate the relationship between psychosocial factors and cancer risk by addressing several shortcomings of prior meta-analyses

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06–1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04–1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers

Global warming and Bergmann’s rule: do central European passerines adjust their body size to rising temperatures?

Recent climate change has caused diverse ecological responses in plants and animals. However, relatively little is known about homeothermic animals’ ability to adapt to changing temperature regimes through changes in body size, in accordance with Bergmann’s rule. We used fluctuations in mean annual temperatures in south-west Germany since 1972 in order to look for direct links between temperature and two aspects of body size: body mass and flight feather length. Data from regionally born juveniles of 12 passerine bird species were analysed. Body mass and feather length varied significantly among years in eight and nine species, respectively. Typically the inter-annual changes in morphology were complexly non-linear, as was inter-annual variation in temperature. For six (body mass) and seven species (feather length), these inter-annual fluctuations were significantly correlated with temperature fluctuations. However, negative correlations consistent with Bergmann’s rule were only found for five species, either for body mass or feather length. In several of the species for which body mass and feather length was significantly associated with temperature, morphological responses were better predicted by temperature data that were smoothed across multiple years than by the actual mean breeding season temperatures of the year of birth. This was found in five species for body mass and three species for feather length. These results suggest that changes in body size may not merely be the result of phenotypic plasticity but may hint at genetically based microevolutionary adaptations