Selfies of Twitter Data Stream through the Lens of Information Theory: A Comparative Case Study of Tweet-trails with Healthcare Hashtags

Little research in information system has been carried out on the subject of user’s choice of different components when composing a tweet through the analytical lens of information theory. This study employs a comparative case study approach to examine the use of hashtags of medical-terminology versus lay-language in tweet-trails and (1) introduces a novel H(x) index to reveal the complexity in the statistical structure and the variety in the composition of a tweet-trail, (2) applies radar graph and scatter plot as intuitive data visualization aids, and (3) proposes a methodological framework for structural analysis of Twitter data stream as a supplemental tool for profile analysis of Twitter users and content analysis of tweets. This systematic framework is capable of unveiling patterns in the structure of tweet-trails and providing quick and preliminary snap shots (selfies) of Twitter data stream because it’s an automatic and objective approach which requires no human intervention

Spinal column shortening versus revision detethering for recurrent adult tethered cord syndrome: a preliminary comparison of perioperative and clinical outcomes.

OBJECTIVE:Recurrent tethered cord syndrome (TCS), believed to result from tension on the distal portion of the spinal cord, causes a constellation of neurological symptoms. Detethering surgery has been the traditional treatment for TCS. However, in cases of recurrent TCS, there is a risk of new neurological deficits developing, and subsequent retethering is difficult to prevent. Spinal column shortening has been proposed as an alternative technique to reduce the tension on the spinal cord without incurring the morbidity of revision surgery on the spinal cord. The authors compared the perioperative outcomes and morbidity of patients who were treated with one or the other procedure. METHODS:The medical records of 16 adult patients with recurrent TCS who were treated between 2005 and 2018 were reviewed. Eight patients underwent spinal column shortening, and 8 patients underwent revision detethering surgery. Patient demographics, clinical outcomes, and perioperative factors were analyzed. The authors include a video to illustrate their technique of spinal column shortening. RESULTS:Within the spinal column shortening group, no patients experienced any complications, and all 8 patients either improved or stabilized with regard to lower-extremity and bowel and bladder function. Within the revision detethering group, 2 patients had worsening of lower-extremity strength, 3 patients had worsening of bowel and bladder function, and 1 patient had improvement in bladder function. Also, 3 patients had wound-related complications. The median estimated blood loss was 731 ml in the shortening group and 163 ml in the revision detethering group. The median operative time was 358 minutes in the shortening group and 226 minutes in the revision detethering group. CONCLUSIONS:Clinical outcomes were comparable between the groups, but none of the spinal column shortening patients experienced worsening, whereas 3 of the revision detethering patients did and also had wound-related complications. Although the operative times and blood loss were higher in the spinal column shortening group, this procedure may be an alternative to revision detethering in extremely scarred or complex wound revision cases

Multi-Device Task-Oriented Communication via Maximal Coding Rate Reduction

Task-oriented communication offers ample opportunities to alleviate the communication burden in next-generation wireless networks. Most existing work designed the physical-layer communication modules and learning-based codecs with distinct objectives: learning is targeted at accurate execution of specific tasks, while communication aims at optimizing conventional communication metrics, such as throughput maximization, delay minimization, or bit error rate minimization. The inconsistency between the design objectives may hinder the exploitation of the full benefits of task-oriented communications. In this paper, we consider a specific task-oriented communication system for multi-device edge inference over a multiple-input multiple-output (MIMO) multiple-access channel, where the learning (i.e., feature encoding and classification) and communication (i.e., precoding) modules are designed with the same goal of inference accuracy maximization. Instead of end-to-end learning which involves both the task dataset and wireless channel during training, we advocate a separate design of learning and communication to achieve the consistent goal. Specifically, we leverage the maximal coding rate reduction (MCR2) objective as a surrogate to represent the inference accuracy, which allows us to explicitly formulate the precoding optimization problem. We cast valuable insights into this formulation and develop a block coordinate descent (BCD) solution algorithm. Moreover, the MCR2 objective also serves the loss function of the feature encoding network, based on which we characterize the received features as a Gaussian mixture (GM) model, facilitating a maximum a posteriori (MAP) classifier to infer the result. Simulation results on both the synthetic and real-world datasets demonstrate the superior performance of the proposed method compared to various baselines.Comment: submitted to IEEE for possible publicatio