Generic framework for the personal omni-remote controller using M2MI

A Generic Framework for the Personal Omni-Remote Controller Using M2MI is a master’s thesis outlining a generic framework for the wireless omni-remote controller that controls neighboring appliances by using Many-to-Many Invocation (M2MI). M2MI is an object-oriented abstraction of broadcast communication. First, this paper introduces the history of remote controllers and analyzes omni-remote controller projects made by other researchers in this area, such as the Pebbles PDA project at Carnegie Mellon University and HP’s COOLTOWN project. Second, this paper depicts a generic framework of the personal omni-remote controller system including architecture, type hierarchy, and service discovery. In this framework, a module approach and a decentralized dual-mode service discovery scheme are introduced. When users request a certain type of service, their omni-remote controller application will first discover the available appliances in the vicinity and then bring up the corresponding control module for the target appliance. Thus, users can control the appliance through the User Interface of the control module. To join the omni-remote controller system, servers and clients need to follow the type hierarchy convention of the system. Finally, several implementations are given to show the control of different appliances with different capabilities. These appliances include thermostats, TVs with parental control, and washing machines

Physiology and Pathophysiology of CLC-1: Mechanisms of a Chloride Channel Disease, Myotonia

The CLC-1 chloride channel, a member of the CLC-channel/transporter family, plays important roles for the physiological functions of skeletal muscles. The opening of this chloride channel is voltage dependent and is also regulated by protons and chloride ions. Mutations of the gene encoding CLC-1 result in a genetic disease, myotonia congenita, which can be inherited as an autosmal dominant (Thomsen type) or an autosomal recessive (Becker type) pattern. These mutations are scattered throughout the entire protein sequence, and no clear relationship exists between the inheritance pattern of the mutation and the location of the mutation in the channel protein. The inheritance pattern of some but not all myotonia mutants can be explained by a working hypothesis that these mutations may exert a “dominant negative” effect on the gating function of the channel. However, other mutations may be due to different pathophysiological mechanisms, such as the defect of protein trafficking to membranes. Thus, the underlying mechanisms of myotonia are likely to be quite diverse, and elucidating the pathophysiology of myotonia mutations will require the understanding of multiple molecular/cellular mechanisms of CLC-1 channels in skeletal muscles, including molecular operation, protein synthesis, and membrane trafficking mechanisms

A Visual Analytic Study of Articles in Entrepreneurship Research

The entrepreneurship research grows continuously in this century; this study utilized the visual analytic method to depict literature characteristics of entrepreneurship research, including publication countries, subject area, most cited references and so on. The analytical data was collected from database of Social Science Citation Index (SSCI) of ISI Web of knowledge. This study provided the several findings to describe the academic trend in entrepreneurship research

THE EFFECT OF EIGHT WEEKS TRAINING WITH EXTRA WEIGHT ON STANDING LONG JUMP PERFORMANCE

The purpose of this study was to investigate the effect of eight weeks training with extra weight in the hands on standing long jump performance. Fifteen junior high school male students participated in the study. Vicon motion system (10 cameras, 200Hz) and two Kistler force plates (1000 Hz) were used to collect the kinematics and kinetic data of pretraining and post-training tests. The results found the jumping distance increased 18 % after extra weight training. The horizontal velocity of center of mass (CM) at takeoff, flight distance, landing distance, the CM difference at takeoff, the horizontal positive impulse and the peak horizontal ground reaction force were all significantly enhanced. It was concluded that eight weeks of extra weight in the hands jump training increased the high school male standing long jump performance

Real value prediction of protein solvent accessibility using enhanced PSSM features

<p>Abstract</p> <p>Background</p> <p>Prediction of protein solvent accessibility, also called accessible surface area (ASA) prediction, is an important step for tertiary structure prediction directly from one-dimensional sequences. Traditionally, predicting solvent accessibility is regarded as either a two- (exposed or buried) or three-state (exposed, intermediate or buried) classification problem. However, the states of solvent accessibility are not well-defined in real protein structures. Thus, a number of methods have been developed to directly predict the real value ASA based on evolutionary information such as position specific scoring matrix (PSSM).</p> <p>Results</p> <p>This study enhances the PSSM-based features for real value ASA prediction by considering the physicochemical properties and solvent propensities of amino acid types. We propose a systematic method for identifying residue groups with respect to protein solvent accessibility. The amino acid columns in the PSSM profile that belong to a certain residue group are merged to generate novel features. Finally, support vector regression (SVR) is adopted to construct a real value ASA predictor. Experimental results demonstrate that the features produced by the proposed selection process are informative for ASA prediction.</p> <p>Conclusion</p> <p>Experimental results based on a widely used benchmark reveal that the proposed method performs best among several of existing packages for performing ASA prediction. Furthermore, the feature selection mechanism incorporated in this study can be applied to other regression problems using the PSSM. The program and data are available from the authors upon request.</p

The design and investigation of nanocomposites containing dimeric nematogens and liquid crystal gold nanoparticles with plasmonic properties showing a nematic-nematic phase transition (Nᵤ-Nₓ/Ntb)

The construction of liquid crystal compositions consisting of the dimeric liquid crystal, CB_C9_CB (cyanobiphenyl dimer = 1",9"-bis(4-cyanobiphenyl-4'-yl)nonane), and the range of nematic systems is explored. The materials include a laterally functionalized monomer, which was used to construct a phase diagram with CB_C9_CB, as well as one laterally linked dimer liquid crystal material and two liquid crystal gold nanoparticle (LC-Au-NPs) systems. For the Au-NP-LCs, the NP diameters were varied between ~3.3 nm and 10 nm. Stable mixtures that exhibit a nematic-nematic phase transition are reported and were investigated by POM (polarizing optical microscopy), DSC (differential scanning calorimetry) and X-ray diffraction studies

Intra-abdominal abscess caused by toothpick injury

SummaryWe present the case of a 42-year-old female who presented to our emergency department (ED) complaining of epigastric pain for four days. She had been seen in the outpatient department and ED previously for evaluation, but continued to experience epigastric pain with fever. Emergency panendoscopy was performed and a toothpick was discovered impacted in the duodenal bulb. The gastroenterologist was unable to remove the toothpick endoscopically. Computed tomography of the abdomen revealed a long and straight hyperdense foreign body, and intra-abdominal abscess formation. An emergency laparotomy was performed. The patient recovered gradually and was discharged 11 days later. She could not remember when she swallowed the wooden toothpick, but guessed that it was while out drinking. There is an old wives’ tale in Taiwan that putting a toothpick in the cup while drinking beer reduces the likelihood of abdominal distention from the carbonation of the beer

Combining Coauthorship Network and Content for Literature Recommendation

This paper studies literature recommendation approaches using both content features and coauthorship relations of articles in literature databases. Most literature databases allow data access (via site subscription) without having to identify users, and thus task-focused recommendation is more appropriate in this context. Previous work mostly utilizes content and usage log for making task-focused recommendation. More recent works start to incorporate coauthorship network for recommendation and found it beneficial when the specified articles preferred by authors are similar in their content. However, it was also found that recommendation based on content features achieves better performance under other circumstances. Therefore, in this work we propose to incorporate both content and coauthorship network in making task-focused recommendation. Three hybrid methods, namely switching, proportional, and fusion are developed and compared. Our experimental results show that in general the proposed hybrid approach achieves better performance than approaches that utilize only one source of knowledge. In particular, the fusion method tends to have higher recommendation accuracy for articles of higher ranks. Besides, the content-based approach is more likely to recommend articles of low fidelity, whereas the coauthorship network-based approach has the least chance

EVALUATION OF RECEIVING ABILITY OF TEENAGE MALE TABLE TENNIS PLAYERS IN TAIWAN

The purpose of this study was to evaluate the forehand receiving ability of teenage male table tennis players. Thirty-nine male players consist of skill levels from junior to senior high school students and national squads were selected. This assessment involves three tests: basic control, judgment, and match-like condition simulation. We found under the basic control test, the junior high school players performed poorer in downspin and left-side downspin in the aspect of accuracy (

NYCU-TWO at Memotion 3: Good Foundation, Good Teacher, then you have Good Meme Analysis

This paper presents a robust solution to the Memotion 3.0 Shared Task. The goal of this task is to classify the emotion and the corresponding intensity expressed by memes, which are usually in the form of images with short captions on social media. Understanding the multi-modal features of the given memes will be the key to solving the task. In this work, we use CLIP to extract aligned image-text features and propose a novel meme sentiment analysis framework, consisting of a Cooperative Teaching Model (CTM) for Task A and a Cascaded Emotion Classifier (CEC) for Tasks B&C. CTM is based on the idea of knowledge distillation, and can better predict the sentiment of a given meme in Task A; CEC can leverage the emotion intensity suggestion from the prediction of Task C to classify the emotion more precisely in Task B. Experiments show that we achieved the 2nd place ranking for both Task A and Task B and the 4th place ranking for Task C, with weighted F1-scores of 0.342, 0.784, and 0.535 respectively. The results show the robustness and effectiveness of our framework. Our code is released at github.Comment: De-Factify 2: Second Workshop on Multimodal Fact Checking and Hate Speech Detection, co-located with AAAI 202