ON THE EQUIVALENCE OF IMPORT TARIFF AND QUOTA: THE CASE OF RICE IMPORT IN TAIWAN

This paper extends the existing theory on the equivalence of import tariff and quota. If the equivalence is defined on the domestic price level (weak equivalence), then either the zero conjectural variation for domestic country or a perfectly competitive market will be sufficient to support this equivalence. If the equivalence is defined both on the same domestic price level as well as tariff rate (strong equivalence), then the conditions are that either domestic country acts as a Cournot competitor and foreign country is a price taker, or both domestic and foreign country are price takers. An empirical spatial-equilibrium trade model is constructed to simulate the impacts of import tariff and quota. Using Taiwan¡¦s rice import as an example, the empirical results show that if Taiwan switches from the quota system to tariff system, the domestic rice price as well as total social welfare can be increased given the same import volume.International Relations/Trade,

Double-Acting, Locking Carabiners

A proposed design for carabiners (tether hooks used in mountaineering, rock climbing, and rescue) is intended to make it possible to operate these devices even while wearing thick gloves. According to the proposal, the gate of a carabiner would be capable of swinging either toward or away from the hook body, relative to the closed position. The gate would be spring-biased to return to the closed position. An external locking collar would be pinned to an internal locking rod that would be springloaded to slide the collar longitudinally over the gate to lock the gate in the closed position. The gate would be unlocked by sliding the collar axially against the spring load. To reduce the probability of inadvertent unlocking, the rod-and-collar mechanism would include two locking buttons. Optionally, the rod-and-collar mechanism could be replaced with an external locking mechanism based on a longer collar

Is Contract Farming More Profitable and Efficient Than Non-Contract Farming-A Survey Study of Rice Farms In Taiwan

Trade liberalization and globalization has modernized the food retail sector in Taiwan, affecting consumers, producers and trade patterns. These changes have placed significant pressures on farmers and processors including more stringent quality control and product varieties. The government has launched a rice production-marketing contract program in 2005 to assist rice farmers and the agro-business sector to work together as partners. The minimum scale for each contract is 50 hectares of adjacent rice paddies with 50 participants including rice farmers, seedling providers, millers and marketing agents. In order to evaluate the outcome of this program, a survey is conducted in the summer of 2005 after the first (spring) crop is harvested. Information of price and value of output and major variable and fixed inputs are collected along with characteristics of the farmers and farms. The survey results show that the average revenue of a contract farm is about 11 percent higher than an average non-contract farm. The per hectare cost of production in a contract farm is about 13 percent lower and as a result the average profit margin under contract is more than 50 percent above those without contract. A swtiching regression profit frontier model is adopted to further investigate their efficiency performance. The result indicates that an average contract farms is 20 percent more efficient than an average non-contract farm in a comparable operating environment. The result also suggests that although contract farming has potential to improve the profit of smallholders, it is not a sufficient condition for such improvement.Land Economics/Use,

ZigBee Wireless Sensor Nodes with Hybrid Energy Storage System Based on Li-Ion Battery and Solar Energy Supply

Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system

ZigBee Wireless Sensor Nodes with Hybrid Energy Storage System Based on Li-Ion Battery and Solar Energy Supply

Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system

ZigBee Wireless Sensor Nodes with Hybrid Energy Storage System Based on Li-Ion Battery and Solar Energy Supply

Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system

D4AM: A General Denoising Framework for Downstream Acoustic Models

The performance of acoustic models degrades notably in noisy environments. Speech enhancement (SE) can be used as a front-end strategy to aid automatic speech recognition (ASR) systems. However, existing training objectives of SE methods are not fully effective at integrating speech-text and noisy-clean paired data for training toward unseen ASR systems. In this study, we propose a general denoising framework, D4AM, for various downstream acoustic models. Our framework fine-tunes the SE model with the backward gradient according to a specific acoustic model and the corresponding classification objective. In addition, our method aims to consider the regression objective as an auxiliary loss to make the SE model generalize to other unseen acoustic models. To jointly train an SE unit with regression and classification objectives, D4AM uses an adjustment scheme to directly estimate suitable weighting coefficients rather than undergoing a grid search process with additional training costs. The adjustment scheme consists of two parts: gradient calibration and regression objective weighting. The experimental results show that D4AM can consistently and effectively provide improvements to various unseen acoustic models and outperforms other combination setups. Specifically, when evaluated on the Google ASR API with real noisy data completely unseen during SE training, D4AM achieves a relative WER reduction of 24.65% compared with the direct feeding of noisy input. To our knowledge, this is the first work that deploys an effective combination scheme of regression (denoising) and classification (ASR) objectives to derive a general pre-processor applicable to various unseen ASR systems. Our code is available at https://github.com/ChangLee0903/D4AM

Paxillin facilitates timely neurite initiation on soft-substrate environments by interacting with the endocytic machinery.

Neurite initiation is the first step in neuronal development and occurs spontaneously in soft tissue environments. Although the mechanisms regulating the morphology of migratory cells on rigid substrates in cell culture are widely known, how soft environments modulate neurite initiation remains elusive. Using hydrogel cultures, pharmacologic inhibition, and genetic approaches, we reveal that paxillin-linked endocytosis and adhesion are components of a bistable switch controlling neurite initiation in a substrate modulus-dependent manner. On soft substrates, most paxillin binds to endocytic factors and facilitates vesicle invagination, elevating neuritogenic Rac1 activity and expression of genes encoding the endocytic machinery. By contrast, on rigid substrates, cells develop extensive adhesions, increase RhoA activity and sequester paxillin from the endocytic machinery, thereby delaying neurite initiation. Our results highlight paxillin as a core molecule in substrate modulus-controlled morphogenesis and define a mechanism whereby neuronal cells respond to environments exhibiting varying mechanical properties

Factors that influence survival in colorectal cancer with synchronous distant metastasis

AbstractBackgroundTreatments for the purposes of curing or more effectively managing metastatic colorectal cancer (CRC) are evolving. Our study focused on patients with primary CRC with synchronous distant metastasis, and we analyzed the factors influencing patient survival.MethodsData review was conducted retrospectively. Clinicopathological parameters included age, sex, site of primary cancer, tumor cell differentiation, number of liver metastasis, presence of extrahepatic metastasis, treatment of liver metastasis, pre-treatment carcinoembryonic antigen (CEA) level, status of treatment response, salvage treatment and survival.ResultsA total of 420 patients were identified and considered for our study. Of those, 275 patients (65.4%) had liver-only metastasis, 100 patients (23.8%) had concomitant lung metastasis, and 40 patients (9.5%) had other metastases. Additionally, 145 patients (34.5%) had liver-directed treatment including surgical resection (28.5%), radiofrequency ablation (RFA) (10.6%) and transcatheter arterial chemoembolization (TAE) (1.2%). There were 80 patients (19%) with CEA levels < 10, 135 patients (32.1%) with CEA 10–100, and 165 patients (39.2%) with CEA > 100. There were 200 patients (47.6%) who had received chemotherapy, 130 patients (30.9%) with target therapy, and 40 patients (9.5%) who had not undergone any salvage treatment. Three significant factors were identified, including treatment of liver metastasis (p=0.027), pre-treatment CEA (p=0.04), and salvage treatment (p=0.005).ConclusionWe demonstrated three factors influencing patient survival including treatment of liver metastasis, pre-treatment CEA level, and salvage treatment. Aggressive treatment of liver metastasis including surgical resection or RFA combined with chemotherapeutic agents appear to provide an increased rate of survival to patients