Quality of fish preparation served in catering establishments of Bombay

The results of the study carried out on the quality of fish preparations served in catering establishments of Bombay revealed that there is no serious potential health hazard to the consumer. Pathogens like Salmonella and Clostridium per were found to be absent. Based on organoleptic, biochemical and bacteriological parameters the quality of fish curry was better than that of fish fry. Overall quality of samples from grade I establishments was better in comparison with grade II and III. However, a few samples of poor quality were also observed in grade I. Extraneous matter like hair and dead housefly were observed in a few samples from grade III indicating poor handling practices. The importance of good hygiene and sanitary practices in catering establishments is discussed.

Quality of certain ready-to-eat fish products of the domestic trade

Quality of 181 samples of ready-to-eat fish products comprising fried fish, fish curry and fish/prawn pickles collected from Cochin and Calicut were studied. Salmonella was absent in all the samples. V. cholerae was tested in the samples collected at Cochin and was absent in all the cases. Coliforms, E. coli, faecal streptococci and coagulase-positive staphylococci were present in some of the samples studied. The study indicated the necessity to improve the sanitary and hygienic conditions of the hotels engaged in the preparation of these products. The study further indicated that fried fish and fish curry shall not be served after 6 hours of their preparation. Added care is to be exercised in the selection of shrimps and fish for the preparation of pickles.

Quality of fish in retail markets of Bombay

Study carried out on the quality of fresh fish in retail markets of Bombay revealed that only 75% of the samples were of acceptable quality. Incidence of faecal streptococci was generally high, indicating poor sanitary and hygienic practices in handling of fresh fish. Total bacterial counts higher than Indian standard specified limits were observed in more than one third of the samples analysed. 7.5% of the samples were found to be contaminated either with Salmonella or Clostridium perfringens, thus posing a serious potential health hazard to the consumer. The quality of fish in different markets is also discussed. The urgent need for formulation and implementation of quality standards for fresh fish in domestic trade is highlighted.

Quality of commercial frozen boiled clam meat

The bacterial quality and sand content of commercial frozen boiled clam meat are discussed. In general the commercial frozen boiled clam meat belonging to the Villorita cyprinoides sp. collected from Cochin are highly contaminated with faecal indicator and pathogenic organisms than that belonging to the Katelysia opima sp. collected from Quilon. The studies also show that the bacterial quality of frozen boiled clam meat can be improved by enforcing better hygienic and sanitary practices.

Study ectoparasite infestation of 10 common imported freshwater ornamental fish species

In the present study, ectoparasite infestation of common freshwater ornamental fish species imported into Iran including: Dwarf gourami (Colisa lalia), Angelfish (Pterophyllum scalare), Oscar (Astronatus ocellatus), Red eye Tetra ( Moenkhansia Sanctaefilomenae), Barb( Capoeta tetrazona), Arowana (Osteoglossum bicirrhosum), Goldfish(Carassius auratus), Red fin Shark (Lebeo elythrurus, Catfish (Hypostomus plecostomus) and Pangasius sutchi ( Pangasius hypophthalmus) from May until April was investigated.A total of 6 specimens sample of each fish species) randomly were obtained and taken alive to the lab. After observing gill and skin wet smear under the microscope , gill was dissected and examined carefully .Photo and films were taken from the isolated parasites and parasite identification was performed according to Yamaguti AP1), Bychowsky (■Y).From a total of examined fishes 1\ ► sample (YY.V.) were parasitized .Parasite groups that were observed consisting ciliated protozoan myxosporidian , monogenean Digenean metacercaria and crustacean .The only non-parasitized fish was Barb. Monogenea Trianchoratus sp. , Cleidodiscus sp. , Ancylodiscoides sp. , Thaparocleidus sp. , Centrocestus formosanus metacercaria and Myxobolus longisporus report for the first time in ornamental fish which imported from Southeast of Asia to Iran. According to the results, it seems that severe quarantine and sanitary rules are necessary.

云南大山包黑颈鹤(Grus nigricollis)越冬行为和保护研究

从2006 年10 月24 日至2007 年4 月9 日，采用固定样线法和瞬时扫描法， 对在大山包国家级自然保护区（N27°18′38″～27°29′15″，E103°14′55″～103°23′49″） 内越冬的黑颈鹤种群进行了越冬行为、日间活动节律和越冬栖息地利用的详细调 查，同时对黑颈鹤的春季迁徙行为和冬季黑颈鹤的死亡现象进行了观察和分析。 这些研究有助于我们了解黑颈鹤是采取何种行为模式和栖息地利用模式来适应高 海拔、低温度的环境，同时对如何有效地保护越冬黑颈鹤和合理规划保护区功能 区域有重要的指导作用。 将黑颈鹤的越冬行为分为：取食（Feeding）、搜寻（Searching）、警戒（Vigilance）、 争斗（Fight）、行走（Walk）、飞行（Flight）、休整（Maintenance）和其它（Others） 八种，越冬期间最主要的行为是取食（53.05±4.93）％，其它行为依次为：搜寻 （10.38±1.34）％、警戒（18.75±2.65）%、休整（10.32±4.93）％、行走（4.90±1.59） ％、飞行（1.70±0.38）％、争斗（0.36±0.25）％、其它（0.55±0.41）％。单因素 方差分析（One-Way ANOVA）分析表明越冬期间黑颈鹤日间各时间段（1h）和各 月份间行为差异极显著（P<0.05），并呈现出规律的变化。黑颈鹤的取食、警戒、 搜寻行为具明显的早（10:00-11:00）、晚（17:00-18:00）两个活动高峰，中午 13:00~14:00 最低；而休整行为正好相反，呈现出中午高峰、上午和下午低谷的趋 势；另外几种行为节律性表现不明显。黑颈鹤越冬期主要行为的节律变化是受环 境温度变化影响的，温度高时黑颈鹤增加了修整时间减少了取食时间，而温度低 时则减少了修整时间增加了取食时间以维持能量需求，湿度是通过温度对黑颈鹤 产生影响的。每天黑颈鹤都随着太阳的升起开始觉醒，于07:18±0:15 飞离夜栖地， 大雾的天气影响了黑颈鹤的外出觅食，与之相适应的是黑颈鹤相应的推迟了出飞 时间。黑颈鹤所采取的所有行为都表现出了对大山包特殊环境的适应。 在大山包黑颈鹤所利用的栖息共有耕地（farmland）、草地（grassland）、沼泽 （marsh）和浅水水域（water area）四类。选择指数分析表明黑颈鹤对水域有极大 的偏好，其次为沼泽湿地，再次为耕地，而对草地表现为负选择，并且在越冬期 间的各月份之间，对不同栖息利用比率保持一致。这提示我们在进行保护区规划 的时候应该适当增加前三种栖息地的面积以满足黑颈鹤的越冬需求。主成份因子 分析表明黑颈鹤倾向于选择距夜栖地和水源较近、人流较少、干扰较小、无坡或缓坡的低海拔栖息地。处于不同越冬地的越冬黑颈鹤根据当地的实际情况采取不 同的栖息地利用，说明黑颈鹤具有较强的环境适应能力。 调查期间记录到了三只带有彩环的黑颈鹤个体，其中有两只佩戴有卫星发射 器，发射器编号分别为64309 和64311。大山包黑颈鹤种群数量变动的春季和秋季 高峰是由于处于不同越冬地的黑颈鹤迁徙造成的，同时也说明了大山包是在滇东 北和黔西北越冬的黑颈鹤的集散地。黑颈鹤的春季迁徙一般集中在3 月下旬至4 月上旬，在晴朗、微风的上午10:00-11:00 迁徙的黑颈鹤数量最多，说明了天气条 件对黑颈鹤迁徙的重要性。 大山包保护区内的高压输电电线和通信电缆对越冬黑颈鹤构成了极大的威 胁。观察期间共有7 只黑颈鹤因撞上输电电线而死亡，除去一只没有外伤的成体 之外，成幼比例为1:1，大都发生在天气较为恶劣的12 月-2 月之间。发生撞死黑 颈鹤的时候保护区内都有不同程度的大雾笼罩，由于大雾的影响造成可视条件下 降，加之黑颈鹤飞行的机动性差（翼载量大、展弦比不大），造成了黑颈鹤的伤亡.

听力障碍与听力正常群体视觉注意发展及其机制的比较

One of the most important functions in the individual development is the interaction and integration of each sensory input. There exist two competing theories, i.e. the deficiency theory and the compensatory theory, regarding the origin and nature of changes in visual functions observed after auditory deprivation. The deficiency theory proposed that integrative processes are essential for normal development. In contrast, the compensatory theory stated that the loss of one sense may be met by a greater reliance upon, therefore an enhancement of the remaining senses. Given that hearing impaired children’s learning depends primarily on visual information, it is important to recognize the differences of visual attention between them and their hearing age-mates. Differences among age groups could exist in either selectivity or sustained attention. Study 1 and study 2 explored the selective and sustained attention development of hearing impaired and hearing students with average cognitive ability, aged from 7 years to college students. The analysis and discussion of the results are based on the visual attention development as well as deficiency theory and compensatory theory. According to the results of the study 1 and study 2, the spatial distribution and controlling of the visual attention between hearing impaired and hearing students were also investigated in the study 3 and study 4. The present work showed that: Firstly, both hearing impaired and hearing participants had the similar developmental trajectory of the sustained attention. The ability of children’s sustained attention appeared to improve with age, and in adolescence it reached the peak. The hearing impaired participants had the comparable sustained attention skills to the matched hearing ones. Besides, the results of the hearing impaired participants showed that they could maintain their attention and vigilance on the current task over the observation period. Secondly, group differences of visual attention development were found between hearing impaired and hearing participants. In the childhood, the visual attention developmental speed of the hearing impaired children was slower than that of the hearing ones. The selective attention skill of the hearing impaired were not comparable to the hearing ones, however, their selective skill improved with age, so in the adulthood, hearing impaired students showed the slight advantage in the selective attention skill over the hearing ones. Thirdly, hearing impaired and hearing participants showed the similar spatial distribution in the attention resources. In the low perceptual load condition, both participants were suffered great interference of the distrator at the fixation. In contrast, in the high perceptual load condition, hearing impaired adults were suffered more interference of the peripheral distractor, which suggested that they distributed more attention resources to the peripheral field when faced difficult tasks. Fourthly, both groups showed similar processing in the visual attention tasks. That is, they both searched the target with only the color feature in a parallel way, but in a serial way while processing orientation feature and the features with the combination of the color and orientation. Furthermore, the results indicated that two groups show similar ways in the attention controlling. In summary, the present study showed that visual attention development was dependent upon the integration of multimodal sensory information. Because of the interaction and integration of the input from various sensory, it has a negative impact on the intact sensory at the early stage of one sensory loss, however, it can better the functions of other intact sensory gradually with development and practice.

Representations and evolutionary operators for the scheduling of pump operations in water distribution networks.

Reducing the energy consumption of water distribution networks has never had more significance. The greatest energy savings can be obtained by carefully scheduling the operations of pumps. Schedules can be defined either implicitly, in terms of other elements of the network such as tank levels, or explicitly by specifying the time during which each pump is on/off. The traditional representation of explicit schedules is a string of binary values with each bit representing pump on/off status during a particular time interval. In this paper, we formally define and analyze two new explicit representations based on time-controlled triggers, where the maximum number of pump switches is established beforehand and the schedule may contain less switches than the maximum. In these representations, a pump schedule is divided into a series of integers with each integer representing the number of hours for which a pump is active/inactive. This reduces the number of potential schedules compared to the binary representation, and allows the algorithm to operate on the feasible region of the search space. We propose evolutionary operators for these two new representations. The new representations and their corresponding operations are compared with the two most-used representations in pump scheduling, namely, binary representation and level-controlled triggers. A detailed statistical analysis of the results indicates which parameters have the greatest effect on the performance of evolutionary algorithms. The empirical results show that an evolutionary algorithm using the proposed representations improves over the results obtained by a recent state-of-the-art Hybrid Genetic Algorithm for pump scheduling using level-controlled triggers.

A toolkit approach to solar radiation modelling.

Considerable effort is required to implement solar radiation models in software. Many existing implementations have efficiency as their main priority rather than re-usability, and this can adversely affect their further development since the relationships between the software and physical quantities may be obscured. The Solar Toolkit is an attempt to overcome such barriers by exploiting the current abundance of computing resource, and the availability of user-oriented tools such as Microsoft Excel®. The Solar Toolkit takes the form of a set of functions written in Visual Basic for Applications® (VBA) made available under the Academic Free Licence. Transparency is the overriding priority throughout the implementation so that the Toolkit can provide a platform for further modelling initiatives.

Solar photovoltaic system applications: a guidebook for off-grid electrification.

Presenting a complete guide for the planning, design and implementation of solar PV systems for off-grid applications, this book features analysis based on the authors’ own laboratory testing as well as their in the field experiences. Incorporating the latest developments in smart-digital and control technologies into the design criteria of the PV system, this book will also focus on how to integrate newer smart design approaches and techniques for improving the efficiency, reliability and flexibility of the entire system. The design and implementation of India’s first-of its-kind Smart Mini-Grid system (SMG) at TERI premises, which involves the integration of multiple renewable energy resources (including solar PV) through smart controllers for managing the load intelligently and effectively is presented as a key case study. Maximizing reader insights into the performance of different components of solar PV systems under different operating conditions, the book will be of interest to graduate students, researchers, PV designers, planners, and practitioners working in the area of solar PV design, implementation and assessment.

Spikes, Synchrony, and Attentive Learning by Laminar Thalamocortical Circuits

This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, and learning. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.

Neural Pattern Recognition on Multichannel Input Representation

This article presents a new neural pattern recognition architecture on multichannel data representation. The architecture emploies generalized ART modules as building blocks to construct a supervised learning system generating recognition codes on channels dynamically selected in context using serial and parallel match trackings led by inter-ART vigilance signals.

Fuzzy ART

Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP synthesize fuzzy logic and ART networks by exploiting the formal similarity between the computations of fuzzy subsethood and the dynamics of ART category choice, search, and learning. Fuzzy ART self-organizes stable recognition categories in response to arbitrary sequences of analog or binary input patterns. It generalizes the binary ART 1 model, replacing the set-theoretic: intersection (∩) with the fuzzy intersection (∧), or component-wise minimum. A normalization procedure called complement coding leads to a symmetric: theory in which the fuzzy inter:>ec:tion and the fuzzy union (∨), or component-wise maximum, play complementary roles. Complement coding preserves individual feature amplitudes while normalizing the input vector, and prevents a potential category proliferation problem. Adaptive weights :otart equal to one and can only decrease in time. A geometric interpretation of fuzzy AHT represents each category as a box that increases in size as weights decrease. A matching criterion controls search, determining how close an input and a learned representation must be for a category to accept the input as a new exemplar. A vigilance parameter (p) sets the matching criterion and determines how finely or coarsely an ART system will partition inputs. High vigilance creates fine categories, represented by small boxes. Learning stops when boxes cover the input space. With fast learning, fixed vigilance, and an arbitrary input set, learning stabilizes after just one presentation of each input. A fast-commit slow-recode option allows rapid learning of rare events yet buffers memories against recoding by noisy inputs. Fuzzy ARTMAP unites two fuzzy ART networks to solve supervised learning and prediction problems. A Minimax Learning Rule controls ARTMAP category structure, conjointly minimizing predictive error and maximizing code compression. Low vigilance maximizes compression but may therefore cause very different inputs to make the same prediction. When this coarse grouping strategy causes a predictive error, an internal match tracking control process increases vigilance just enough to correct the error. ARTMAP automatically constructs a minimal number of recognition categories, or "hidden units," to meet accuracy criteria. An ARTMAP voting strategy improves prediction by training the system several times using different orderings of the input set. Voting assigns confidence estimates to competing predictions given small, noisy, or incomplete training sets. ARPA benchmark simulations illustrate fuzzy ARTMAP dynamics. The chapter also compares fuzzy ARTMAP to Salzberg's Nested Generalized Exemplar (NGE) and to Simpson's Fuzzy Min-Max Classifier (FMMC); and concludes with a summary of ART and ARTMAP applications.

ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network

This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.