Species losses, gains, and changes in persistent species are associated with distinct effects on ecosystem functioning in global grasslands

Global change drivers such as anthropogenic nutrient inputs simultaneously alter biodiversity, species composition, and ecosystem functions such as above ground biomass. These changes are interconnected by complex feedbacks among extinction, invasion, and shifting relative abundance. Here, we use a novel temporal application of the Price equation to separate species richness and biomass change through time and quantify the functional contributions of species that are lost, gained, and persist under ambient and experimental nutrient addition in 59 global grasslands. Under ambient conditions, compositional and biomass turnover was high, but species losses (i.e., local extinctions) were balanced by gains (i.e. colonization). Under fertilization, there was biomass loss associated with species loss. Few species were gained in fertilized conditions over time but those that were, and species that persisted, contributed to net biomass gains, outweighing biomass loss. These components of community change are associated with distinct effects on measures of ecosystem functioning.

Invariant odor recognition with ON–OFF neural ensembles

Invariant stimulus recognition is a challenging pattern-recognition problem that must be dealt with by all sensory systems. Since neural responses evoked by a stimulus are perturbed in a multitude of ways, how can this computational capability be achieved? We examine this issue in the locust olfactory system. We find that locusts trained in an appetitive-conditioning assay robustly recognize the trained odorant independent of variations in stimulus durations, dynamics, or history, or changes in background and ambient conditions. However, individual- and population-level neural responses vary unpredictably with many of these variations. Our results indicate that linear statistical decoding schemes, which assign positive weights to ON neurons and negative weights to OFF neurons, resolve this apparent confound between neural variability and behavioral stability. Furthermore, simplification of the decoder using only ternary weights ({+1, 0, −1}) (i.e., an “ON-minus-OFF” approach) does not compromise performance, thereby striking a fine balance between simplicity and robustness.

Nanoscale Chemical Imaging of Coadsorbed Thiolate Self-assembled Monolayers on Au(111) by Tip-Enhanced Raman Spectroscopy

Self-assembled monolayers (SAMs) of thiolates on metal surfaces are of key importance for engineering surfaces with tunable properties. However, it remains challenging to understand binary thiolate SAMs on metals at the nanoscale under ambient conditions. Here we employ tip-enhanced Raman spectroscopy (TERS) and density functional theory (DFT) calculations to investigate local information of binary SAMs on Au(111) coadsorbed from an equimolar mixture of p-cyanobenzenethiol (pCTP) and p-aminothiophenol (pATP), including chemical composition, coadsorption behavior, phase segregation, plasmon-induced photocatalysis, and solvation effects. We found that upon competitive adsorption of pCTP and pATP on Au(111) from a methanolic solution, the coadsorption initially occurs randomly and homogeneously; eventually, pATP is replaced by pCTP through gradual growth of pCTP nanodomains. TERS imaging also allows for visualization of the plasmon-induced coupling of pATP to p,p’-dimercaptoazobenzene (DMAB) and the solvation-induced phase segregation of the binary SAMs into nanodomains, with a spatial resolution of ~9 nm under ambient conditions. According to DFT calculations, these aromatic thiolates differing only in their functional groups, -CN versus –NH2, show different adsorption energy on Au(111) in vacuum and methanol, and thus the solvation effect on adsorption energy of these thiolates in methanol can determine the dispersion state and replacement order of the binary thiolates on Au(111).

Droplet Flow Assisted Electrocatalytic Oxidation of Selected Alcohols under Ambient Condition

This study reports using a droplet flow assisted mechanism to enhance the electrocatalytic oxidation of benzyl alcohol, 2-phenoxyethanol, and hydroxymethylfurfural at room temperature. Cobalt phosphide (CoP) was employed as an active electrocatalyst to promote the oxidation of each of the individual substrates. Surface analysis of the CoP electrocatalyst using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), as well as electrochemical characterization, revealed that it had excellent catalytic activity for each of the substrates studied. The combined droplet flow with the continuous flow electrochemical oxidation approach significantly enhanced the conversion and selectivity of the transformation reactions. The results of this investigation show that at an electrolysis potential of 1.3 V and ambient conditions, both the selectivity and yield of aldehyde from substrate conversion can reach 97.0%.

Postharvest Losses in Quantity and Quality of Pear (cv. Packham’s Triumph) along the Supply Chain and Associated Economic, Environmental and Resource Impacts

Approximately one third of the food produced globally is lost or wasted along the supply chain. Reducing this would be an important measure to increase the global food supply as the world continues the struggle to feed its people sustainably. Not merely a waste of food, these losses also represent a waste of human effort and agricultural inputs from expensive fertilizers to natural resources as well as contributing to global greenhouse gas emissions. Measuring the extent of, and understanding the reasons for, these losses can assist in developing appropriate measures required to prevent or reduce such losses. Therefore, the objective of this research was to quantify postharvest losses in quantity and quality of ‘Packham’s Triumph’ pears at farm and simulated retail levels. Pears were sampled from two farms in the Western Cape Province of South Africa, the largest deciduous fruit production and export region in Southern Africa. The greatest losses measured along the supply chain were on-farm immediately after harvest, with 18% recorded. The main reasons for on-farm losses were small size (65%), deformity (26%), and chafed peel (9%). After 14 days in cold storage (−0.3 ± 0.7 °C, 81.3 ± 4.1% RH), mean pear losses were 0.86% which increased to 1.49% after 28 days. After 10 days of further storage under simulated market conditions (5.4 ± 0.6 °C, 83.7 ± 2.9% RH), fruit losses were 1.52% during retail marketing and 2.09% during export. Storing pears under ambient conditions (25.1 ± 1.3 °C and 46.6 ± 6.0% RH) resulted in a higher incidence of losses, increasing from 0.90 to 1.55 and 2.25% after 3, 7, and 10 days, respectively. The socio-economic impacts of these postharvest losses amounted to financial losses of between ZAR 492 million (USD 34.1 million according to the conversion rate of 14 April 2021) to over ZAR 831 million annually, and this was associated with the loss of 301 million MJ of fossil energy, 69 million m3 of fresh water and contributed to the emission of approximately 19,690 tons of CO2 equivalent. The fresh water lost could sustain 3.7 million individuals daily for a whole year at a daily minimum usage rate of 0.05 m3 per day while it will require planting 0.5 million trees to sink the 19,690 tons GHG emissions of the pear losses (0.039 metric ton per urban tree planted). Decreasing postharvest losses will conserve resources as well as improve food security and nutrition, objectives of the post-2015 sustainable development agenda led by the United Nations.

Wearable Device for Observation of Physical Activity with the Purpose of Patient Monitoring Due to COVID-19

In late 2019, a new genre of coronavirus (COVID-19) was first identified in humans in Wuhan, China. In addition to this, COVID-19 spreads through droplets, so quarantine is necessary to halt the spread and to recover physically. This modern urgency creates a critical challenge for the latest technologies to detect and monitor potential patients of this new disease. In this vein, the Internet of Things (IoT) contributes to solving such problems. This paper proposed a wearable device that utilizes real-time monitoring to detect body temperature and ambient conditions. Moreover, the system automatically alerts the concerned person using this device. The alert is transmitted when the body exceeds the allowed temperature threshold. To achieve this, we developed an algorithm that detects physical exercise named “Continuous Displacement Algorithm” based on an accelerometer to see whether a potential temperature rise can be attributed to physical activity. The people responsible for the person in quarantine can then connect via nRF Connect or a similar central application to acquire an accurate picture of the person’s condition. This experiment included an Arduino Nano BLE 33 Sense which contains several other sensors like a 9-axis IMU, several types of temperature, and ambient and other sensors equipped. This device successfully managed to measure wrist temperature at all states, ranging from 32 °C initially to 39 °C, providing better battery autonomy than other similar devices, lasting over 12 h, with fast charging capabilities (500 mA), and utilizing the BLE 5.0 protocol for data wireless data transmission and low power consumption. Furthermore, a 1D Convolutional Neural Network (CNN) was employed to classify whether the user is feverish while considering the physical activity status. The results obtained from the 1D CNN illustrated the manner in which it can be leveraged to acquire insight regarding the health of the users in the setting of the COVID-19 pandemic.

Design of a Highly Efficient Wideband Multi-Frequency Ambient RF Energy Harvester

For low input radio frequency (RF) power from −35 to 5 dBm, a novel quad-band RF energy harvester (RFEH) with an improved impedance matching network (IMN) is proposed to overcome the poor conversion efficiency and limited RF power range of the ambient environment. In this research, an RF spectral survey was performed in the semi-urban region of Malaysia, and using these results, a multi-frequency highly sensitive RF energy harvester was designed to harvest energy from available frequency bands within the 0.8 GHz to 2.6 GHz frequency range. Firstly, a new IMN is implemented to improve the rectifying circuit’s efficiency in ambient conditions. Secondly, a self-complementary log-periodic higher bandwidth antenna is proposed. Finally, the design and manufacture of the proposed RF harvester’s prototype are carried out and tested to realize its output in the desired frequency bands. For an accumulative −15 dBm input RF power that is uniformly universal across the four radio frequency bands, the harvester’s calculated dc rectification efficiency is about 35 percent and reaches 52 percent at −20 dBm. Measurement in an ambient RF setting shows that the proposed harvester is able to harvest dc energy at −20 dBm up to 0.678 V.

Role of Aluminum and Lithium in Mitigating Alkali-Silica Reaction—A Review

Effective mitigation of alkali-silica reaction (ASR) is critical for producing durable concrete. The use of alumina-rich supplementary cementitious materials (SCMs) and chemical admixtures such as lithium salts to prevent expansion caused by ASR was first reported 70 years ago, shortly after the discovery of ASR in 1940s. Despite numerous investigations, the understanding of the mechanisms of Al and Li for mitigating ASR remain partially inexplicit in the case of Al, and hardly understood in the case of Li. This paper reviews the available information on the effect of Al and Li on ASR expansion, the influencing factors, possible mechanisms and limitations. The role of Al in mitigating ASR is likely related to the reduction of dissolution rate of reactive silica. Moreover, the presence of Al may alter the structure of crystalline ASR products to zeolite or its precursor, but such effect seems to be not that significant at ambient conditions due to the slow kinetics of zeolite formation. Several mechanisms for the lithium salts in mitigating ASR have been proposed, but most of them are not conclusive primarily due to the lack of knowledge about the formed reaction products. Combination of Al-rich SCMs and lithium salts may be used as an economic solution for ASR mitigation, although systematic studies are necessary prior to the applications.