Miracle-dz/UniFAR-FTUs huggingface dataset:
Change and Diversity in Smallholder Rice-Fish Systems: Recent Evidence from Bangladesh

Efforts to unlock the genetic potential of both rice and fish, when combined with efforts to improve the management of riceâ€“fish systems, have considerable proven potential for increasing agricultural productivity and food security. In Bangladesh, estimates suggest that the countryâ€™s potential riceâ€“fish production system encompasses between two and three million hectares of land. Despite three decades of research on biophysical and technical aspects of riceâ€“fish systems, this potential has not been realized fully due to insufficient attention given to the social, economic, and policy dimensions of system improvement. This paper provides a characterization of the diverse and changing nature of riceâ€“fish systems in Bangladesh by combining data from a novel upazilla-level (sub-district-level) survey of fishery officers with household surveys, focus group discussions, and a meta-review of the literature on aquaculture in the country. The resulting analysis sheds new light on the economic viability of different riceâ€“fish systems and recommends policy and investment options to further improve the development and delivery of riceâ€“fish technologies. Findings indicate that in addition to concurrent riceâ€“fish systems, alternating riceâ€“fish systems and collectively managed systems offer considerable potential for increasing productivity and farm incomes in Bangladesh. Findings also suggest that although the emergent innovation system around these riceâ€“fish systems is fairly dynamic, there is a need for more supportive policies and investmentsâ€”and analysis of the intended and unintended impacts of these policies and investments.
Advances and Challenges in Cytomegalovirus Detection Methods for Liver Transplant Donors

Cytomegalovirus (CMV) infection is a highly prevalent opportunistic infection among liver transplant recipients. When the liver donor is infected with CMV, there is a risk of transmission to the recipient, leading to CMV infection. To improve the postoperative outcome of liver transplantation, it is crucial to shift the focus of CMV detection to the donor and achieve early diagnosis, as well as implement effective preventative and therapeutic measures. However, the commonly used CMV detection methods in the past had limitations that prevented their early and accurate diagnosis in liver transplant donors. This review focuses on the latest advancements in CMV detection methods that can potentially be applied to liver transplant donors. The objective is to compare and evaluate their clinical utility, thereby providing guidance and support for rapid and accurate diagnosis of CMV infection in the clinic. The clustered regularly interspaced short palindromic repeats-associated proteins (CRISPR–Cas) system-based assay emerges as a promising method for detecting the virus, offering great prospects for early and expedient CMV infection diagnosis in clinical settings.
Efficient Edge Data Management Framework for IIoT via Prediction-Based Data Reduction

Large amounts of time series data are required to support data analysis at the edge in the end-edge-cloud Industrial Internet of Things (IIoT) architecture. Reducing the storage cost is one of the main challenges in edge data management due to the limited storage resource of edge nodes. The state-of-the-art data reduction method has a high time overhead and poor reduction efficiency for unstable data sets. To solve this problem, this study proposes a time-series data management framework that combines data partition and data compression techniques. For the data partition technique, we propose an adaptive selection strategy to integrate the access pattern of the application and the characteristics of the time series data, thereby improving the partition accuracy. For the data compression technique, we propose a compression scheme based on time series data segmentation by using the idea of divide and conquer; we further introduce a change point detection technique to improve the compression efficiency for unstable data sets. Experimental results obtained with three types of real industrial data sets show that our framework is significantly better than the state-of-the-art method in terms of compression ratio and time overhead.
PD-1/PD-L1 Inhibitors plus Chemotherapy Versus Chemotherapy Alone for Resectable Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Simple Summary Immunotherapy, particularly programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors, has been responsible for changing the natural history of advanced or metastatic non-small cell lung cancer. However, its use in the resectable stage is not yet fully elucidated. Therefore, we aimed to evaluate the efficacy and safety of neoadjuvant and adjuvant use of PD-1/PD-L1 inhibitors plus chemotherapy versus chemotherapy alone in resectable stage (I-III) non-small cell lung cancer. Our findings suggest that the incorporation of PD-1/PD-L1 inhibitors alongside chemotherapy offers a promising prospect for reshaping the established treatment paradigms for patients diagnosed with resectable stages of non-small cell lung cancer. Abstract Background: The benefit of adding programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors to the treatment of early-stage non-small cell lung cancer (NSCLC), both neoadjuvant therapy (NAT) and adjuvant therapy (AT), is not yet fully elucidated. Methods: We searched PubMed, Embase, and Cochrane databases for randomized controlled trials (RCT) that investigated PD-1/PD-L1 inhibitors plus chemotherapy for resectable stage NSCLC. We computed hazard ratios (HRs) or odds ratios (ORs) for binary endpoints, with 95% confidence intervals (CIs). Results: A total of seven RCTs comprising 3915 patients with resectable stage NSCLC were randomized to chemotherapy with or without PD-1/PD-L1 inhibitors as NAT or AT. As NAT, the PD-1/PD-L1 inhibitors plus chemotherapy group demonstrated significantly improved overall survival (HR 0.66; 95% CI 0.51–0.86) and event-free survival (HR 0.53; 95% CI 0.43–0.67) compared with the chemotherapy alone group. There was a significant increase in favor of the PD-1/PD-L1 inhibitors plus chemotherapy group for major pathological response (OR 6.40; 95% CI 3.86–10.61) and pathological complete response (OR 8.82; 95% CI 4.51–17.26). Meanwhile, as AT, disease-free survival was significant in favor of the PD-1/PD-L1 inhibitors plus chemotherapy group (HR 0.78; 95% CI 0.69–0.90). Conclusions: In this comprehensive systematic review and meta-analysis of RCTs, the incorporation of PD-1/PD-L1 inhibitors alongside chemotherapy offers a promising prospect for reshaping the established treatment paradigms for patients diagnosed with resectable stages of NSCLC. Moreover, our analyses support that neoadjuvant administration with these agents should be encouraged, in light of the fact that it was associated with an increased survival and pathological response, at the expense of a manageable safety profile.
Potential impacts of climate change on agricultural land use suitability: barley

A relatively simple model was developed to generate climate change scenarios for a variety of agricultural crops. The model was only partially validated against real data, hence it is best used as a decision support system that allows people with land resource, crop and climate knowledge to determine potential impacts of climate change on crop growth and production. Land use capability data and climate information for the agricultural zone of Western Australia were combined with a modified French and Schultz equation to produce a potential yield map for canola. Another yield map was then produced for 2050 based on SRES marker scenario A2, CSIRO Mark II, which is considered a good model for the South West of Western Australia.
Assessment Of Industrial Waste and Additives Materials Use in The Sustainable Design of Concrete

The sustainable design of concrete is of paramount importance in the construction industry as it strives to minimize environmental impact while maintaining performance and durability. A key aspect of this endeavor is the assessment and integration of industrial waste materials and additives into concrete formulations. Concrete is the most frequently used construction material in the world. Each year, over ten billion tonnes of concrete are produced, resulting in the depletion of natural resources and a colossal carbon footprint. One of the primary objectives of contemporary concrete technology is to reduce the use of Portland cement and natural fine aggregates by partially substituting them with various waste materials and industrial byproducts. This paper summarises the findings of a study in which steel slag aggregate, silica fume and glass refuse were successfully used to partially replace river sand and Portland cement.
Modeling brine inflow to Room Q: A numerical investigation of flow mechanisms

A hydrologic modeling study was performed to gain insight into the flow mechanisms around Room Q. A summary of hydrologic and structural data and of predictive fluid flow models from Room Q are provided. Six years of measured data are available from the time of excavation. No brine accumulation in Room Q was measured in the first two years following excavation. However, there is considerable uncertainty associated with this early-time data due to inadequate sealing of the room. Brine may have been lost to evaporation or it may have flowed into newly created disturbed rock zone (DRZ) porosity resulting from excavation. Non-zero brine accumulation rates were measured from 2--5 years, but brine accumulation within the room dropped to zero after 5.5 years. A conceptual model for brine inflow to Room Q was developed which assumes far-field Darcy flow combined with an increasing DRZ pore volume. Numerical simulations employed TOUGH28W and used predictive DRZ porosity increase with time from SPECTROM-32 rock deformation simulations. Simulated brine inflow showed good agreement with measured brine accumulation rates for the first five years. Two important conclusions were drawn from the simulation results: (1) early-time brine inflow to the room can be reduced to zero if the DRZ pore volume increases with time, and (2) brine accumulation (inflow) rates from 2 to 5 years suggest a far-field permeability of 5 {times} 10{sup {minus}22} m{sup 2} with a bulk rock compressibility of 5.4 {times} 10{sup {minus}12} Pa{sup {minus}1}.
Matching method between nanoparticle displacement agent size and pore throat in low permeability reservoir

Nano-particles possess desirable attributes such as small particle size, excellent injectivity, and migration performance, making them highly compatible and adaptable for addressing the water flooding requirements of the low-permeability oil reservoir. When selecting an oil displacement agent for enhancing water flooding and improving oil recovery, factors such as injectivity and migration need to be carefully considered. In this study, through a comprehensive analysis of the mechanism and technical characteristics of nano-particle oil displacement agents, the plugging and profile control mechanisms recognized by the mainstream of nano-particles are elucidated. By examining various elements including outcrop fractures, natural micro-fractures, artificial support fractures, and dynamic monitoring data, a reevaluation of the dominant channel scale governing water drive in low permeability reservoirs is conducted, thereby defining the target entities for profile control and flooding operations. Drawing upon Darcy’s percolation law and leveraging enhanced oil recovery techniques based on the classical Kozeny equation, a profile control and flooding mechanism is proposed that focuses on increasing the specific surface area of polymer particles while simultaneously reducing reservoir permeability. This innovative approach establishes a novel matching method between nano-polymer particles and the diverse media found within the reservoir. Lastly, the application of nanoparticle flooding technology in Changqing Oilfield is presented, highlighting its practical implementation and benefits.
Biogenic Ice Nuclei: Part I. Terrestrial and Marine Sources

Abstract Decayed plant leaf litters from North America, Europe and Asia have been found to contain copious numbers of ice nuclei, some active at −4°C. The abundance of nuclei in a litter was noted to vary according to the climate of the plant's origin; litters from tropical, A-type climates (according to the Koppen classification) contain fewer ice nuclei (103 g−1 active at −10°C) than litters from mid-latitude, C-type climates (105 g−1 active at −10°C) which in turn contain fewer nuclei than litters from high-latitude, D-type climates (109 g−1 at −10°C). The rate of release of freezing nuclei to the atmosphere from in situ litters from D-type climates was determined experimentally: the flux of nuclei active at −12°C was found to be 101−103 cm−2 day−1 during daylight hours. Active ice nuclei also have been found in seawaters rich in phytoplankton; seawaters devoid of plankton are poor sources of ice nuclei. Some of these nuclei are active at temperatures around −4°C and concentrations reach up to 107−103 .
Sobel filter and linear classification for deepfake analysis of faces

Through artificial intelligence (AI) techniques, deepfakes (deep learning + fakes) are created. Currently, almost six years after this topic's popularization, some people have been using AI algorithms to change, for example, face. In this scenario, this article proposes to identify the most discriminating characteristics, based on the multivariate statistical learning techniques, with and without the Sobel filter. Complementarily, we aim to analyze the areas that humans have visually identified as relevant to detect a deepfake. The results show that the statistical model (PCA plus MLDA) combined with the Sobel filter correctly classified most of the images, highlighting the regions that discriminate a deepfake.
Temporal dependence of burn severity assessment in Siberian larch (Larix sibirica) forest of northern Mongolia using remotely sensed data

Assessing burn severity is critical for understanding both the short- and long-term effects of fire disturbance on forest ecosystems. This study proposed a methodology to reconstruct burn severity from the Landsat imagery at different time lags after a fire (≤18 years) in Siberian larch (Larix sibirica) forest. The estimated accuracy of the burn severity models we developed indicated strong effects of forest recovery, image acquisition date and remote sensing predictors on the burn severity assessment. In the first several years after the fire, the dNBR (differenced Normalized Burn Ratio) was the most important remotely sensed index for assessing burn severity, followed by the dNDMI (differenced Normalized Difference Moisture Index) and dNDVI (differenced Normalized Difference Vegetation Index). However, the dNDMI was more important than the dNBR and dNDVI in explaining burn severity when larch forest regrowth dominated. The overall accuracy of the classification and regression tree models showed a decrease in accuracy from 83% to 62% depending on the lag times of burn severity assessment. The high severity class had the lowest omission and commission errors, followed by the low and moderate classes among lag times. Our evaluation of model transferability and thresholds of burn severity index demonstrates the advantage of the proposed methodology for rapid assessment of fire effects in boreal larch forest that will assist in understanding the complex relationships among forest fires and ecological processes in Eurasian boreal ecosystems.
Probabilistic Prediction of the US Great Recession with Historical Experts

Some prominent economic experts have contended that (the early stages of) the Great Recession resembled the Great Depression. In this paper, we utilize an expert-based framework to produce probabilistic projections for output growth and in ation during the recent slump. We divide our US data prior to the Great Recession into ve distinct historical eras. Each expert estimates a vector autoregressive model (VAR) on data from a unique era, with epoch dates re ecting conventional timing assumptions adopted in the economic history literature. We nd that our Great Depression expert performs relatively well in terms of the logarithmic score averaged over the out of sample evaluation period from 2005Q1 to 2010Q4, when compared to a benchmark VAR estimated on Great Moderation data. However, other experts are competitive individually, along with a combination of experts from different eras. Given the Great Depression expert's forecast densities have statistically significant predictive content for output growth and in ation over the evaluation period, we investigate economic significance by adopting a cost-loss ratio approach. We find that the Great Depression expert outperforms the Great Moderation benchmark provided that unanticipated negative output growth events are relatively costly. More generally, for both output growth and for low in ation events, the Great Depression expert fails to beat the benchmark. Unfortunately, the Great Depression expert's projections lack confidence|stemming from the many uncertainties in the Great Depression era. Even for negative output growth events, the Great Depression expert gives too many false alarms. More confident historical experts, such as Bretton Woods, perform better overall. Hence, although the Great Depression helps predict the Great Recession, from a probabilistic perspective, other historical eras have economic relevance.
Knowledge and Awareness of Glaucoma Among People Living in Taif City in the Western Region of Saudi Arabia

Background Glaucoma represents a significant global health challenge, characterized by progressive and irreversible optic nerve damage, visual field impairment, and potential blindness. Limited awareness can lead to delayed diagnosis and increased healthcare burden. This research explored glaucoma awareness in Taif City, Saudi Arabia. It delved into the influence of demographics, socioeconomic factors, and cultural beliefs on awareness. The study aimed to inform tailored awareness campaigns and policy decision-makers about regional awareness, ultimately contributing to effective healthcare initiatives in the region. Methodology A cross-sectional study was conducted in Taif City including adults (>18 years) using a community-based approach. Data were collected using an electronic questionnaire. Results This study included 1,000 participants. Most participants were males, aged 18-29 years, with 51.1% (n = 511) having at least a bachelor’s education. The media (n = 341, 34.1%) and relatives/friends (n = 336, 33.6%) were common sources of glaucoma information. Among all participants, 58.5% (n = 585) had heard of glaucoma, and many were uncertain about glaucoma’s definition and normal eye pressure values. About 63.1% (n = 631) believed in a cure, and 43.1% thought vision loss could be restored. Gender, education, and family history significantly influenced awareness. Closed-angle glaucoma (n = 297, 29.7%) and open-angle glaucoma (n = 231, 23.1%) were recognized types, with surgery (n = 371, 37.1%) and laser treatment (n = 274, 27.4%) perceived as potential cures. Conclusions This study revealed glaucoma awareness among adults in Taif City. Gender, education, and family history played significant roles in shaping awareness levels. There is a need for targeted educational efforts to improve knowledge about glaucoma in the community.
Echolocation call characterization of insectivorous bats from caves and karst areas in southern Luzon Island, Philippines

Bats are excellent bioindicators and are increasingly used to assess ecosystem health and monitor changes in the environment. Due to increased awareness of the potential transmission of pathogens from bats to humans and recognizing the limitations of traditional bat sampling methods, the use of of non-invasive sampling techniques such as bat recorders were recommended for field-based monitoring studies. In the Philippines, however, bat bioacoustics is still a growing field, and the scarcity of acoustic data hinders the use of echolocation calls to conduct accurate inventories and population monitoring of echolocating bats. Here, we recorded and characterized echolocation calls of insectivorous bats from caves and karst areas located in southern Luzon Island, Philippines. In addition, we compared our results with other studies performed within and outside the country to identify possible regional and local variation in acoustic characters for some species. A total of 441 echolocation calls were recorded from six bat families: Hipposideridae (five species), Rhinolophidae (five species), Vespertilionidae (three species), Miniopteridae (two species), Megadermatidae (one species), and Emballonuridae (one species). Discriminant function analyses (DFA) with leave-one-out cross validation correctly classified bats emitting calls dominated with a constant frequency (CF) component (rhinolophids and hipposiderids) with >97% success and those producing frequency modulated (FM) calls (Miniopteridae and Vespertilionidae) with 88.9% success. We report echolocation calls for Philippine population of two species (Megaderma spasma and Hipposideros lekaguli) for the first time. Moreover, we present geographical variations in call frequencies for some species by comparing previously reported acoustic data elsewhere across the species’ range. This underscores the importance of establishing a readily accessible and comprehensive local reference library of echolocation calls which would serve as a valuable resource for examining taxonomic identities of echolocating bats, particularly those whose calls exhibit biogeographic variations.
Reducing Annual Cow Cost by Grazing Windrowed Millet

The objective was to determine whether grazing millet stored in windrows is a viable alternative to baling and feeding hay to beef cows. Sixty spring-calving heifers (458 kg, 5.9 BCS) were randomly allotted to windrow grazing or bale feeding to determine whether performance would differ between treatments. Research was conducted from November 5, 1997 to January 8, 1998. Millet was planted in early July and harvested in early September. Two fields were paired into similarly yielding strips, which were either baled or left as windrows. Small square bales from the baled strips were weighed to estimate forage amounts in the windrows of similarly yielding strips. Field 1 (19.7 ha) was divided into six sections, three baled and three left as windrows. Field 2 (2.1 ha) was divided into one baled section and one section left as windrows. Treatments were: 1) windrow grazing with forage allocation controlled to 13.2 kg·heifer−1·d−1 by moving a temporary fence daily, and 2) daily bale feeding of 13.2 kg·heifer−1·d−1. Heifer weight and BCS were measured at the beginning, d 28, d 56, and the end of the study. Weight or BCS change was not different for any time period (P>0.10). Forage samples were collected every 2 wk for analysis. Differences in forage nutrient composition were found based on storage method. Overall, similar cow performance was attained, whereas the costs of baling and feeding hay were eliminated by grazing the windrows.