Modeling Risk Behavior of Agricultural Production in Chinese Small Households

This paper analyzed Chinese small-scale farmer's response to agricultural risks by using MOTAD model. Based on the household's data from the two villages Wangjia and Damao in Zhejiang province, we established "representative rural household" for each of the sampling villages. The results show that farmers in Zhejiang are quite sensitive to agricultural risks. However, different farming systems, the ratio of agricultural income to total family income, as well as the size of arable land, differentiates their risk response. The decision maker's risk preference not only affects the type of agricultural activities and corresponding scales they selected, but also have further effects on the micro agricultural production structure and stable growth of household's income. Given the amount of productive resources such as arable land, capital and labor force, the combination of production activities with a higher level of expected income/risk would be selected if the decision maker is willing to take risks. In a higher level of risks, capital is invested prior to manpower, implying that the latter has a much higher opportunity cost. For those combinations with a lower risk level, diversification might reduce risks to some extent at a cost of total return. Current agriculture structure needs to be adjusted and improved.Farming household, agricultural risks, risk response, MOTAD Model, Farm Management, Risk and Uncertainty, D1, C6, D2,

Atroposelective Chiral-at-Rhodium Catalysis and Nitrene-Mediated Enantioselective Synthesis of Chiral α-Amino Acids with Ruthenium and Iron Catalysts

The interface of asymmetric and transition metal catalysis has greatly boosted the advancement of synthetic chemistry, especially in the context of an increasing demand of chiral organic molecules in various fields. In the past decade, our group developed a series of structurally unique chiral-at-metal complexes which have exhibited excellent catalytic reactivity and stereocontrol for catalyzing a series of asymmetric reactions. This thesis aims at exploring more application and tackling several previously unsolved challenges for employing such chiral-at-metal complexes in asymmetric catalysis. Chapter 2. A catalytic protocol for the synthesis of axially chiral 2,5-disubstituted N-arylpyrroles is described. The method relies on the atroposelective alkylation at the C5-position of 2-monosubstituted N-arylpyrrole substrates by the electrophilic alkylating reagent N-acryloyl-1H-pyrazole. The bis-cyclometalated chiral-at-rhodium complex RhS serves as the chiral Lewis acid catalyst which is able to discriminate the interconvertible conformations of the starting materials. The reaction affords the products in up to 93 % yield and with up to ]99.5 % e.e., using catalyst loadings that could be lowered to 0.05 mol%. The reaction is suitable of synthesizing structurally diverse N-arylpyrroles by the merits of excellent functional group tolerance and versatile transformations of acylpyrazole moiety. The reaction represents the first example of atroposelective reactions catalyzed by the bis-cyclometalated chiral-at-rhodium complexes. Chapter 3. Regio- and stereoselectivity issues are often confronted in non-ring-closing asymmetric nitrene C(sp3)‒H insertion reactions. We present a strategy for addressing these issues by covalently connecting the nitrene precursor to the substrate (carboxylic acids). Upon metal-assisted cleavage of the connected nitrene precursor, both reaction fragments are bound to the metal catalyst, which allows the subsequent nitrene C‒H insertion to undergo via highly controlled cyclic transition states and to provide the acyclic amine products in excellent regio- and stereoselectivity. The reaction provides a surprisingly simple access for structurally diverse N-Troc-protected chiral α-amino acids with aryl, alkenyl and alkynyl side chains in up to 96% yield and with up to 99% e.e., from azanyl ester substrates that are readily accessible by high-yielding carbodiimide-coupling of abundant carboxylic acids with V N-Troc-protected hydroxylamines. The reaction represents the first example of highly regio- and stereocontrolled non-ring-closing nitrene C(sp3)–H insertion catalyzed by the C2-symmetric chiral-at-ruthenium complexes, as well as a breakthrough for the catalytic asymmetric synthesis of chiral α-amino acids. Chapter 4. Intermolecular asymmetric nitrene C(sp3)–H insertion is a highly challenging research topic in nitrene chemistry, and to date most reported transformations suffer from low selectivity, inconvenient nitrene precursors, and/or extremely limited substrate scope. We explore an unprecedent mechanistic manifold for nitrene-mediated asymmetric intermolecular C(sp3)–H amination, namely directed nitrene C–H insertion by using deprotonated carboxylic acids as the directing group, which allows the formation of structurally defined cyclic transition states for the highly regioselective hydrogen atom abstraction and subsequent stereoselective C–N bond formation. The reaction is able to directly convert abundant feedstock carboxylic acids into highly valuable non-racemic chiral α-amino acids bearing aryl and alkyl side chains in up to 89% yield and with up to 97% e.e. The synthetic utility of this reaction is further enhanced by the use of carbamate protection groups such as Boc and Troc that are commonly employed in amino acid chemistry. This reaction represents the first example of directed intermolecular C(sp3)–H nitrene insertion and is a general protocol for the synthesis of chiral α-mono- and α,α-disubstituted α-amino acids

Explanation Selection Using Unlabeled Data for Chain-of-Thought Prompting

Recent work has shown how to prompt large language models with explanations to obtain strong performance on textual reasoning tasks, i.e., the chain-of-thought paradigm. However, subtly different explanations can yield widely varying downstream task accuracy. Explanations that have not been "tuned" for a task, such as off-the-shelf explanations written by nonexperts, may lead to mediocre performance. This paper tackles the problem of how to optimize explanation-infused prompts in a blackbox fashion. We first generate sets of candidate explanations for each example in the prompt using a leave-one-out scheme, then find an effective combination of these explanations with a two-stage framework. We first evaluate explanations for each in-context example in isolation according to two proxy metrics, log likelihood and accuracy on new examples. Then, we search over combinations of explanations to find one that yields high performance against a silver-labeled development set. Across four textual reasoning tasks spanning question answering, mathematical reasoning, and natural language inference, results show that our proxy metrics correlate with ground truth accuracy and our overall method can effectively improve prompts over crowdworker annotations and naive search strategiesComment: EMNLP 202

Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks

We investigate the relationship of resting-state fMRI functional connectivity estimated over long periods of time with time-varying functional connectivity estimated over shorter time intervals. We show that using Pearson's correlation to estimate functional connectivity implies that the range of fluctuations of functional connections over short time scales is subject to statistical constraints imposed by their connectivity strength over longer scales. We present a method for estimating time-varying functional connectivity that is designed to mitigate this issue and allows us to identify episodes where functional connections are unexpectedly strong or weak. We apply this method to data recorded from $N=80$ participants, and show that the number of unexpectedly strong/weak connections fluctuates over time, and that these variations coincide with intermittent periods of high and low modularity in time-varying functional connectivity. We also find that during periods of relative quiescence regions associated with default mode network tend to join communities with attentional, control, and primary sensory systems. In contrast, during periods where many connections are unexpectedly strong/weak, default mode regions dissociate and form distinct modules. Finally, we go on to show that, while all functional connections can at times manifest stronger (more positively correlated) or weaker (more negatively correlated) than expected, a small number of connections, mostly within the visual and somatomotor networks, do so a disproportional number of times. Our statistical approach allows the detection of functional connections that fluctuate more or less than expected based on their long-time averages and may be of use in future studies characterizing the spatio-temporal patterns of time-varying functional connectivityComment: 47 Pages, 8 Figures, 4 Supplementary Figure

Continuous-wave and Transient Characteristics of Phosphorene Microwave Transistors

Few-layer phosphorene MOSFETs with 0.3-um-long gate and 15-nm-thick Al2O3 gate insulator was found to exhibit a forward-current cutoff frequency of 2 GHz and a maximum oscillation frequency of 8 GHz after de-embedding for the parasitic capacitance associated mainly with the relatively large probe pads. The gate lag and drain lag of the transistor was found to be on the order of 1 us or less, which is consistent with the lack of hysteresis, carrier freeze-out or persistent photoconductivity in DC characteristics. These results confirm that the phosphorene MOSFET can be a viable microwave transistor for both small-signal and large-signal applications.Comment: Accepted for oral presentation at IMS 201

Global phase diagram of three-dimensional extended Boson Hubbard model - a continuous time Quantum Monte Carlo study

We present the global phase diagram of the extended boson Hubbard model on a simple cubic lattice by quantum Monte Carlo simulation with worm update algorithm. Four kinds of phases are supported by this model, including superfluid, supersolid, Mott, and charge density wave (CDW) states, which are identified in the phase diagram of chemical potential $\mu$ versus nearest neighbor interaction V . By changing the chemical potential, a continuous transition is found from the Mott phase to a superfluid phase without breaking the translational symmetry. For an insulating CDW state, adding particles to it gives rise to a continuous transition to a supersolid phase, while removing particles usually leads to a first-order one to either supersolid or superfluid phase. By tuning the nearest neighbor interaction, one can realize the transition between two insulating phases, Mott and CDW with the same particle density, which turns out to be of the first-order. We also demonstrate that a supersolid phase with average particle density less than 1/2 can exist in a small region of $\mu$ - V phase diagram

Video Prediction by Efficient Transformers

Video prediction is a challenging computer vision task that has a wide range of applications. In this work, we present a new family of Transformer-based models for video prediction. Firstly, an efficient local spatial-temporal separation attention mechanism is proposed to reduce the complexity of standard Transformers. Then, a full autoregressive model, a partial autoregressive model and a non-autoregressive model are developed based on the new efficient Transformer. The partial autoregressive model has a similar performance with the full autoregressive model but a faster inference speed. The non-autoregressive model not only achieves a faster inference speed but also mitigates the quality degradation problem of the autoregressive counterparts, but it requires additional parameters and loss function for learning. Given the same attention mechanism, we conducted a comprehensive study to compare the proposed three video prediction variants. Experiments show that the proposed video prediction models are competitive with more complex state-of-the-art convolutional-LSTM based models. The source code is available at https://github.com/XiYe20/VPTR.Comment: Accepted by Image and Vision Computing. arXiv admin note: text overlap with arXiv:2203.1583