We present a network model of interstate food trade and report comprehensive estimates of embodied irrigation energy and greenhouse gas (GHG) emissions in virtual water trade for the United States (U.S.). We consider trade of 29 food commodities including 14 grains and livestock products between 51 states. A total of 643 million tons of food with a corresponding 322 billion m3 of virtual water, 584 billion MJ of embodied irrigation energy, and 42 billion kg CO2-equivalent GHG emissions were traded across the U.S. in 2012. The estimated embodied GHG emissions in irrigation water are similar to CO2 emissions from the U.S. cement industry, highlighting the importance of reducing environmental impacts of irrigation. While animal-based commodities represented 12% of food trade, they accounted for 38% of the embodied energy and GHG emissions from virtual irrigation water transfers due to the high irrigation embodied energy and emissions intensity of animal-based products. From a network perspective, the food trade network is a robust, well-connected network with the majority of states participating in food trade. When the magnitude of embodied energy and GHG emissions associated with virtual water are considered, a few key states emerge controlling high throughput in the network.

No abstract

Parkinson's disease (PD) is a neurodegenerative disorder that predominantly affects the motor system. Diffusion magnetic resonance imaging (MRI) has demonstrated deficits in anisotropy as well as increased diffusivity in the sub-cortical structures, primarily in the substantia nigra in PD. However, the clinical spectrum of PD is not limited to motor symptoms; rather, it encompasses several nonmotor symptoms such as depression, psychosis, olfactory dysfunction, and cognitive impairment. These nonmotor symptoms underscore PD as a complex neurological disorder arising from dysfunction of several network components. Therefore, to decipher the underlying neuropathology, it is crucial to employ novel network-based methods that can elucidate associations between specific network changes. This study aimed at assessing the large-scale structural network changes in PD. Structural connectomes were computed by using probabilistic fiber tracking on diffusion MRI between 86 regions of interest. Graph theoretic analysis on the connectome was carried out at several levels of granularity: global, local (nodal), lobar, and edge wise. Our findings demonstrate lower network clustering capability, overall lower neural connectivity, and significantly reduced nodal influence of the hippocampus in PD. In addition, extensive patterns of reduced connectivity were observed within and between the temporal, parietal, and occipital areas. In summary, our findings corroborate widespread structural disconnectivity that can be potentially linked to the nonmotor symptoms in PD.

Psychosis, manifested through formed visual hallucinations or minor hallucinations, is a common non-motor symptom of Parkinson's disease (PD). The pathogenesis of psychosis in PD remains unclear; however, is possibly linked to structural and functional alterations in the hippocampus. To explore the role of hippocampus in psychosis, a detailed hippocampal subfield analysis was performed on PD patients with (PD-P) and without psychosis (PD-NP), and healthy controls (HC). An automated subfield parcellation was performed on T1 MRI images of 141 subjects (PD-P:42, PD-NP:51, and HC:48). The volumes of 12 subfields on each side were estimated and analyzed between the three groups and were corrected for multiple comparisons using false discovery rates. The volumes were also correlated to psychosis severity and specific neuropsychological tests and finally were employed to predict the psychosis severity in PD-P using a support vector regression (SVR) model. Compared to controls, PD-NP group did not demonstrate any significant differences; however, the PD-P group had significantly lower total hippocampal volume. Bilateral molecular layer, granule cell-dentate gyrus, left subiculum, and hippocampal tail and right CA3, CA4, and HATA illustrated significantly lower volumes, while bilateral hippocampal fissure demonstrated a significant widening. Compared to PD-NP, the PD-P group had higher volume of the bilateral hippocampal fissures. Finally, SVR could significantly predict the psychosis severity from all the subfield volumes. Our findings indicate a higher degeneration of specific hippocampal subfields in PD-P compared to controls and a trend of higher volume of hippocampal fissures in PD-P group than in PD-NP.

Mobile communication systems are always in continuous evolution due to the demands of the end-users using this technology. Therefore, before the possible launch of 5G, some technologies have opened the way to the new mobile communication system. The need for technologies that provide more comfort to users has led to the construction of complex communication systems that were only science fiction decades ago. The information society in which we are now immersed has been the result of constant progress over time. In this paper, a survey of multiple access schemes for next-generation wireless communication systems is presented. Multiple access schemes are reviewed for possible use in nextgeneration wireless communication systems such as orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA), and delta-orthogonal multiple access (D-OMA), etc. General comparisons of 1G to 6G are presented. Different types of OMA are explained, and then orthogonal frequency division multiple access (OFDMA) is chosen as an example of the OMA scheme to compare with NOMA and D-OMA. There are two types of NOMA: power-domain and code-domain, which are discussed and compared. Simulation results are presented, and a comparison among different access schemes is provided.