Sustainability of New Hampshire\u27s sawmill industry and its forest resource base

Sustaining our forests is vital for a healthy ecosystem and for the future of forest industry. To sustain the regional sawmill industry as well as the associated forest resource base, the key is to track the consumption and inventory of eastern white pine (Pinus strobus L.), the most dominant commercial species in New Hampshire. This research profiled the sawmill industry in New Hampshire and Vermont in terms of production, consumption, labor characteristics and regulating economic and policy issues. We examined the sustainability of the industry and its resource base; with a specific focus on the white pine sawmill industry and the dynamics of its supporting forest resource in New Hampshire by developing a wood supply model. We modeled spatially explicit demand by mills based on procurement data incorporating market forces and simulated inventory, harvest and stumpage prices, for a fifty-year projection period. This is the first approximation of a transparent spread-sheet based timber supply model tracking mill consumption and its forest base inventory at both state and county levels. It tested nine scenarios and corresponding sensitivities to parameter changes. It provided impact assessments of future land use change and other market dynamics on future wood supply for the sawmill industry. Model results suggest that the most sustainable scenario will be the optimistic case with low-end initial mill consumption and the least sustainable scenario will be the pessimistic case with high-end initial mill consumption. Except for the base and the optimistic cases with low-end initial mill consumption, model results forecast general trends of increasing stumpage prices and decreasing inventory, stocking and harvest levels over a 50-year period for eastern white pine in New Hampshire. Policies to absorb the adverse impacts for sustaining a long-term healthy forest industry and its forest resource base are needed. Future works can expand the model fully to more species and integrate a more detailed evaluation at the landscape level of the forest resource base. Key words. forest sustainability, sawmill industry, wood supply

Economics for forest landowners

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UniVTG: Towards Unified Video-Language Temporal Grounding

Video Temporal Grounding (VTG), which aims to ground target clips from videos (such as consecutive intervals or disjoint shots) according to custom language queries (e.g., sentences or words), is key for video browsing on social media. Most methods in this direction develop taskspecific models that are trained with type-specific labels, such as moment retrieval (time interval) and highlight detection (worthiness curve), which limits their abilities to generalize to various VTG tasks and labels. In this paper, we propose to Unify the diverse VTG labels and tasks, dubbed UniVTG, along three directions: Firstly, we revisit a wide range of VTG labels and tasks and define a unified formulation. Based on this, we develop data annotation schemes to create scalable pseudo supervision. Secondly, we develop an effective and flexible grounding model capable of addressing each task and making full use of each label. Lastly, thanks to the unified framework, we are able to unlock temporal grounding pretraining from large-scale diverse labels and develop stronger grounding abilities e.g., zero-shot grounding. Extensive experiments on three tasks (moment retrieval, highlight detection and video summarization) across seven datasets (QVHighlights, Charades-STA, TACoS, Ego4D, YouTube Highlights, TVSum, and QFVS) demonstrate the effectiveness and flexibility of our proposed framework. The codes are available at https://github.com/showlab/UniVTG.Comment: Accepted by ICCV 2023. 16 pages, 10 figures, 13 tables. Code: https://github.com/showlab/UniVT

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Optimization Approaches of Multi-Dimensional Environments in Rural Space Reproduction Driven by Tourism

Rural tourism is an important driving force for the transformation of rural society in the process of urbanization. However, besides promoting rural economy, it also interrupts the development of the rural living, human, manage and economic multi-dimensional environments. Space reconstruction in rural settlements is an important means to optimize multi-dimensional environments and revitalize rural tourism. Focusing on two types of rural settlements, namely the “relocation village” and the “sightseeing and settlement symbiosis village”, this study has revealed the affecting mechanism of space reconstruction in rural tourist locations on the local multi-dimensional environment by establishing a multi-dimensional environment evaluation system through an analytic, hierarchical process. Subsequently, based on the theoretical perspective of the reproduction of the space and the paradigm of the three-fold model, a comprehensive optimization path of rural multi-dimensional environments has been proposed. The results show that in the space reconstruction process driven by tourism: (1) the multi-dimensional environments of the “sightseeing and settlement symbiosis village” generally develop better than the “relocation village”; (2) the ecological environment is the direct benefit while the management environment and economic environment are the bottlenecks; (3) the “sightseeing and settlement symbiosis village” is more appealing to tourists who are interested in rural tourism since it keeps more rustic characteristics than the “relocation village”; (4) in order to optimize the multi-dimensional environments, “relocation village” should pay more attention to the space needs of residents, improve space utilization rates, and increase the residents’ sense of belonging; (5) “sightseeing and settlement symbiosis village” needs to resolve the contradiction between the tourism and living demands, improve the reproduction process driven by diversified entities, and reconstruct the neighborhood network under rural tourism

Optimization of urban scenic spot planning based on ecological chain and reversed-planning theory—Using Yunlong Lake in Xuzhou city as an example

Modernized urban organization relies more on the foundation of ecological infrastructure (EI) with the planning objectives based more on synthetical benefits of economy, society and ecological environment. The effect of multiple factors ought to be taken into consideration in the urban scenic spot planning and and the process of formulating the related plan faces a challenge of how to organically bound environmental factors to tour function of urban scenic spot. This thesis, taking YunLong Lake, a scenic spot in XuZhou, JiangSu province as an example, studies how to ameliorate the planning of urban scenic spot combined with the ecological chain and reversed-planning theory. The result shows that utilizing the theory flexibly when analyzing the urban scenic spot planning design can ensure the existing ecological connection between each system and maintain the ecological stability of urban scenic spot. Thus, with the basis of ecological chain and reversed-planning theory, this paper puts forward a new planning concept and work flow, in order to provide new ideas for modernized urban scenic spot planning

Optimization Approaches of Multi-Dimensional Environments in Rural Space Reproduction Driven by Tourism

Rural tourism is an important driving force for the transformation of rural society in the process of urbanization. However, besides promoting rural economy, it also interrupts the development of the rural living, human, manage and economic multi-dimensional environments. Space reconstruction in rural settlements is an important means to optimize multi-dimensional environments and revitalize rural tourism. Focusing on two types of rural settlements, namely the “relocation village” and the “sightseeing and settlement symbiosis village”, this study has revealed the affecting mechanism of space reconstruction in rural tourist locations on the local multi-dimensional environment by establishing a multi-dimensional environment evaluation system through an analytic, hierarchical process. Subsequently, based on the theoretical perspective of the reproduction of the space and the paradigm of the three-fold model, a comprehensive optimization path of rural multi-dimensional environments has been proposed. The results show that in the space reconstruction process driven by tourism: (1) the multi-dimensional environments of the “sightseeing and settlement symbiosis village” generally develop better than the “relocation village”; (2) the ecological environment is the direct benefit while the management environment and economic environment are the bottlenecks; (3) the “sightseeing and settlement symbiosis village” is more appealing to tourists who are interested in rural tourism since it keeps more rustic characteristics than the “relocation village”; (4) in order to optimize the multi-dimensional environments, “relocation village” should pay more attention to the space needs of residents, improve space utilization rates, and increase the residents’ sense of belonging; (5) “sightseeing and settlement symbiosis village” needs to resolve the contradiction between the tourism and living demands, improve the reproduction process driven by diversified entities, and reconstruct the neighborhood network under rural tourism

Insoles Treated with Bacteria-Killing Nanotechnology Bio-Kil Reduce Bacterial Burden in Diabetic Patients and Healthy Controls

Our study investigated the effectiveness of bacteria-killing nanotechnology Bio-Kil socks on bacterial burden reduction in diabetic patients and healthy individuals. Four strains of S. aureus and four strains of E. coli were cultured and dropped on Bio-Kil socks and control socks for 0 h, 8 h, and 48 h of incubation. Diluted samples were inoculated and bacterial counts were recorded. Additionally, 31 patients with type 2 diabetes and 31 healthy controls were assigned to wear one Bio-Kil sock on one foot and a control sock on the other for four hours, and then they were told to exchange socks from one foot to the other for four hours. The socks were sampled and diluted and then inoculated to record bacterial counts. Bacterial counts were reduced in Bio-Kil socks compared with control socks in all S. aureus strains after 0 h, 8 h, and 48 h of incubation. In E. coli strains, bacterial counts declined in Bio-Kil socks comparing with control socks in most of the experiments with ESBL-negative E. coli and ATCC35218 at 0 h and 48 h of incubation. In all participants, the mean bacterial counts significantly decreased in Bio-Kil socks in comparison with control socks both at 0 h and at 40 h of incubation (p=0.003 at 0 h and p=0.006 at 40 h). Bio-Kil socks from diabetic patients showed significantly lessened bacterial count at 40 h of incubation (p=0.003). In healthy individuals, Bio-Kil socks reflected a significantly smaller mean bacterial count than control socks (p=0.016). Socks using Bio-Kil nanotechnology efficiently reduce bacterial counts in both diabetic patients and healthy individuals and might exert stronger efficacy in Gram-positive bacteria

The Impact of Atmospheric Pollutants on Human Health and Economic Loss Assessment

The impact of air pollution on human health is becoming increasingly severe, and economic losses are a significant impediment to economic and social development. This paper investigates the impact of air pollutants on the respiratory system and its action mechanism by using information on inpatients with respiratory diseases from two IIIA (highest) hospitals in Wuhan from 2015 to 2019, information on air pollutants, and meteorological data, as well as relevant demographic and economic data in China. This paper describes the specific conditions of air pollutant concentrations and respiratory diseases, quantifies the degree of correlation between the two, and then provides a more comprehensive assessment of the economic losses using descriptive statistical methods, the generalized additive model (GAM), cost of illness approach (COI), and scenario analysis. According to the findings, the economic losses caused by PM2.5, PM10, SO2, NO2, and CO exposure are USD 103.17 million, USD 70.54 million, USD 98.02 million, USD 40.35 million, and USD 142.38 million, for a total of USD 454.46 billion, or approximately 0.20% of Wuhan’s GDP in 2019. If the government tightens control of major air pollutants and meets the WHO-recommended criterion values, the annual evitable economic losses would be approximately USD 69.4 million or approximately 0.03% of Wuhan’s GDP in 2019. As a result, the relevant government departments must strengthen air pollution control to mitigate the impact of air pollution on population health and the associated economic losses

Rs46522 in the Ubiquitin-Conjugating Enzyme E2Z Gene Is Associated with the Risk of Coronary Artery Disease in Individuals of Chinese Han Population with Type 2 Diabetes

Aims. We investigated the association between ubiquitin-conjugating enzyme E2Z (UBE2Z) gene SNP rs46522 and the risk of CAD in a Chinese Han population with type 2 diabetes and explored a possible interactive effect with environmental risk factors of CAD. Methods. 665 patients with T2D were enrolled; 390 were CAD patients and 275 were non-CAD patients. Genotype analysis of rs46522 (T>C) was performed using PCR-RFLP. Results. The SNP rs47522 was associated with the risk of CAD supposing recessive inheritance model (TT versus CC+CT, OR′=1.277, 95%CI′ 1.039–1.570, p′=0.020) and codominant model (TT versus CT, OR′=1.673, 95%CI′ 1.088–2.570, p′=0.019) after adjustment for confounders of CAD. A synergistic effect of rs46522 and BMI was discovered (β=0.012, p for interreaction = 0.028). In subgroup analysis, minor allele T was significantly associated with CAD in overweight and obesity subgroup (p=0.034), and the association was also proved in recessive model (OR=1.537, 95%CI 1.075–2.196, p=0.018). Smokers with genotype TT had threefold risk of CAD in comparison to nonsmokers with genotype TC or CC (p<0.001). Conclusions. The SNP rs46522 in UBE2Z gene is associated with the risk of CAD in the individuals of Chinese Han descent with type 2 diabetes and is of synergistic effect with BMI