A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of anomalies --- and then proposing how to simulate and control these factors when sampling points during benchmark creation. We apply this methodology to produce a large corpus of unsupervised anomaly detection benchmarks and then evaluate several state-of-the-art anomaly detection algorithms against this corpus. Our final analysis not only compares the performance of these algorithms across a large variety of problems, but it also assesses the impact of our identified problems dimensions on experimental outcomes

Selector function of MHC I molecules is determined by protein plasticity

The selection of peptides for presentation at the surface of most nucleated cells by major histocompatibility complex class I molecules (MHC I) is crucial to the immune response in vertebrates. However, the mechanisms of the rapid selection of high affinity peptides by MHC I from amongst thousands of mostly low affinity peptides are not well understood. We developed computational systems models encoding distinct mechanistic hypotheses for two molecules, HLA-B*44:02 (B*4402) and HLA-B*44:05 (B*4405), which differ by a single residue yet lie at opposite ends of the spectrum in their intrinsic ability to select high affinity peptides. We used <em>in vivo</em> biochemical data to infer that a conformational intermediate of MHC I is significant for peptide selection. We used molecular dynamics simulations to show that peptide selector function correlates with protein plasticity, and confirmed this experimentally by altering the plasticity of MHC I with a single point mutation, which altered <em>in vivo</em> selector function in a predictable way. Finally, we investigated the mechanisms by which the co-factor tapasin influences MHC I plasticity. We propose that tapasin modulates MHC I plasticity by dynamically coupling the peptide binding region and {\alpha}<sub>3</sub> domain of MHC I allosterically, resulting in enhanced peptide selector function

Promoting climate-smart sustainable agroforestry to tackle social and environmental challenges: The case of macadamia agroforestry in Malawi

Our current global food system is understood to require a fundamental transformation based on a holistic approach to maintain long-term fertility, healthy biodiverse agroecosystems, and climate-proof/secure livelihoods. Recently, there has been a growing recognition of smallholder farmers’ contributions to addressing key global environmental and social development issues, including poverty, food security, climate change, and sustainable development. One specific approach is agroforestry-based agriculture, in which edible food and commercially important trees are grown on cropland, thereby improving the biodiversity of farming systems, enhancing agricultural productivity, and adding benefits such as nutrition and financial stability, not least climate resilience. In this context, we present lessons learned from an agroforestry system in Malawi that involves smallholder farmer cooperatives interplanting macadamia nut trees with annual crops such as groundnuts, maize, and soybeans. We review holistic advantages such as yield improvement, farmer perceptions, and challenges. We provide insights into what works in designing (Neno Macadami Trust and linkage with finance plan) and draw lessons that can be applied to other comparable programmes worldwide

Systematic construction of anomaly detection benchmarks from real data

Research in anomaly detection suffers from a lack of realis-tic and publicly-available problem sets. This paper discusses what properties such problem sets should possess. It then introduces a methodology for transforming existing classi-fication data sets into ground-truthed benchmark data sets for anomaly detection. The methodology produces data sets that vary along three important dimensions: (a) point diffi-culty, (b) relative frequency of anomalies, and (c) clustered-ness. We apply our generated datasets to benchmark several popular anomaly detection algorithms under a range of dif-ferent conditions. 1

Effect of Harvesting Time and Drying Methods on Aflatoxin Contamination in Groundnut in Mozambique

The production and utilization of groundnut have increased tremendously across all provinces of Mozambique. However, the presence of aflatoxins has remained a critical food concern in the human diet. In this study, the effect of harvesting time and drying methods on aflatoxin contamination was examined in Northern Mozambique. A randomized complete block design in a split-split plot arrangement with four replications was used with groundnut varieties as the main plot and harvesting dates and drying methods as the subplots. Groundnut samples were analyzed for aflatoxin using the Mreader. In both locations, field observations indicated that on average, aflatoxin contamination levels were lower at physiological maturity (≤10 ppb) compared to harvesting 10 days before (≤15 ppb) and 10 days after physiological maturity (≥20 ppb). It was also observed that the two drying methods were effective in prevention of aflatoxin contamination on groundnut kernels to levels lower than 20 ppb. Aflatoxin contamination levels were significantly lower (≤12 ppb) as a result of the A-Frame than the tarpaulin method. The results of this study, therefore, have indicated that proper postharvest management of groundnuts, such as harvesting at physiological maturity and improved drying, gave lowest aflatoxin contamination levels

Multiplexed single-cell proteomics using SCoPE2

Many biological systems are composed of diverse single cells. This diversity necessitates functional and molecular single-cell analysis. Single-cell protein analysis has long relied on affinity reagents, but emerging mass-spectrometry methods (either label-free or multiplexed) have enabled quantifying >1,000 proteins per cell while simultaneously increasing the specificity of protein quantification. Here we describe the Single Cell ProtEomics (SCoPE2) protocol, which uses an isobaric carrier to enhance peptide sequence identification. Single cells are isolated by FACS or CellenONE into multiwell plates and lysed by Minimal ProteOmic sample Preparation (mPOP), and their peptides labeled by isobaric mass tags (TMT or TMTpro) for multiplexed analysis. SCoPE2 affords a cost-effective single-cell protein quantification that can be fully automated using widely available equipment and scaled to thousands of single cells. SCoPE2 uses inexpensive reagents and is applicable to any sample that can be processed to a single-cell suspension. The SCoPE2 workflow allows analyzing ~200 single cells per 24 h using only standard commercial equipment. We emphasize experimental steps and benchmarks required for achieving quantitative protein analysis

Climate suitability predictions for the cultivation of macadamia (<i>Macadamia integrifolia</i>) in Malawi using climate change scenarios

Climate change is altering suitable areas of crop species worldwide, with cascading effects on people reliant upon those crop species as food sources and for income generation. Macadamia is one of Malawi’s most important and profitable crop species; however, climate change threatens its production. Thus, this study’s objective is to quantitatively examine the potential impacts of climate change on the climate suitability for macadamia in Malawi. We utilized an ensemble model approach to predict the current and future (2050s) suitability of macadamia under two Representative Concentration Pathways (RCPs). We achieved a good model fit in determining suitability classes for macadamia (AUC = 0.9). The climatic variables that strongly influence macadamia’s climatic suitability in Malawi are suggested to be the precipitation of the driest month (29.1%) and isothermality (17.3%). Under current climatic conditions, 57% (53,925 km2) of Malawi is climatically suitable for macadamia. Future projections suggest that climate change will decrease the suitable areas for macadamia by 18% (17,015 km2) and 21.6% (20,414 km2) based on RCP 4.5 and RCP 8.5, respectively, with the distribution of suitability shifting northwards in the 2050s. The southern and central regions of the country will suffer the greatest losses (≥ 8%), while the northern region will be the least impacted (4%). We conclude that our study provides critical evidence that climate change will reduce the suitable areas for macadamia production in Malawi, depending on climate drivers. Therefore area-specific adaptation strategies are required to build resilience among producers

Farmer preference for macadamia varieties and constraints to production in Malawi

Macadamia nuts constitute a vital component of both nutrition and livelihoods for smallholder producers in Malawi. We conducted a comprehensive mixed-methods study, combining qualitative and quantitative analyses, to explore varietal preferences and production challenges among these farmers. Leveraging cross-sectional data from 144 members of the Highlands Macadamia Cooperative Union Limited, our study underscores several significant findings. Our findings reveal that the majority of smallholder macadamia farmers (62%) are aged over 50, with farming as their primary occupation. Varied preferences are driven by yield-related traits, including high yield potential (38%), nut quality (29%), and extended flowering patterns (15%). Among the macadamia varieties, the top five choices, grown by over half of the farmers, include HAES 660 (18%), 800 (10%), 791 (9%), 816 (8%), and 246 (7%). Additionally, our study identifies five primary constraints faced by smallholder macadamia farmers: insect pests (81%), diseases (34%), limited market access (33%), wind damage (25%), and inadequate agricultural advisory services (17%). Based on these findings, we propose two policy recommendations to enhance smallholder macadamia production and productivity in Malawi. Specifically, we advocate for informed breeding programs that align with farmer preferences to promote greater adoption of macadamia varieties. Additionally, we emphasize the crucial role of the Malawian government in the macadamia value chain, suggesting active participation in providing extension services and marketing support, akin to its support for other cash crops

Factors affecting soil quality among smallholder macadamia farms in Malawi

Declining soil fertility limits smallholder macadamia productivity in Malawi. To reverse this trend, it is essential to apply organic and inorganic fertilisers in an efficient and effective manner. Yet, fertilizer recommendations for smallholder macadamia (Macadamia integrifolia) production in Malawi are not site-specific. Nutrient imbalances can occur if fertilisers are applied without a clear understanding of whether they are required or not. This may lead to yield losses, unnecessary costs, and other environmental issues associated with excess fertiliser application. To address this research need/ knowledge gap, our study examined the current soil fertility status among smallholder macadamia farms in Malawi. Specifically, the objective was to establish an evidence base for promoting soil fertility restoration interventions for smallholder macadamia production. One hundred and eighty nine soil samples at a depth of 0–15 cm were collected from sixty three smallholder macadamia farms belonging to the Highlands Macadamia Cooperative Union Limited members in central and southern Malawi. We found that the majority of the soils were sandy loams (52%), strongly acidic (mean pH ≤ 5.1), and deficient in essential nutrients required for the healthy growth of macadamia. The soils had an average low cation exchange capacity of 1.67 cmol ( +) kg−1, which is inadequate for macadamia cultivation. More than half of the sampled soils had very low organic matter content (≤ 1%). The low soil organic matter content, coupled with the sandy texture and high acidity, contributed to the observed low concentrations of essential nutrients and cation exchange capacity. Poor agronomic practices and inherent soil characteristics are responsible for this low soil fertility. Altogether, our findings underscore the urgent need to identify and implement more sustainable and effective soil nutrient management practices that help to improve the soil fertility of macadamia farms under smallholder systems