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There is a growing demand for indoor positioning systems (IPSs) in a wide range of applications. However, traditional solutions such as GPS face many technical challenges. In recent years, a promising alternative has been emerging, the visible light communication (VLC)-based IPS, which offers a combination of high accuracy, low cost, and energy efficiency. This article presents a comprehensive review of VLC-based IPSs, providing a tutorial-like overview of the system. It begins by comparing various positioning systems and providing background information on their inherent limitations. Experimental results have demonstrated that VLC-based systems can achieve localization accuracy to within 10 cm in controlled environments. The mechanisms of VLC-based IPSs are then discussed, including a comprehensive examination of their performance metrics and underlying assumptions. The complexity, operating range, and efficiency of VLC-based IPSs are examined by analyzing factors such as channel modeling, signal processing, and localization algorithms. To optimize VLC-based IPSs, various strategies are explored, including the design of efficient modulation schemes, the development of advanced encoding and decoding algorithms, the implementation of adaptive power control, and the application of state-of-the-art localization algorithms. In addition, system parameters are carefully examined. These include LED placement, receiver sensitivity, and transmit power. Their impact on energy efficiency and localization accuracy is highlighted. Altogether, this paper serves as a comprehensive guide to VLC IPSs, providing in-depth insights into their vast potential and the challenges that they present.

This paper provides a comprehensive review of the literature concerning the utilization of Natural Language Processing (NLP) techniques, with a particular focus on transformer-based large language models (LLMs) trained using Big Code, within the domain of AI-assisted programming tasks. LLMs, augmented with software naturalness, have played a crucial role in facilitating AI-assisted programming applications, including code generation, code completion, code translation, code refinement, code summarization, defect detection, and clone detection. Notable examples of such applications include the GitHub Copilot powered by OpenAI’s Codex and DeepMind AlphaCode. This paper presents an overview of the major LLMs and their applications in downstream tasks related to AI-assisted programming. Furthermore, it explores the challenges and opportunities associated with incorporating NLP techniques with software naturalness in these applications, with a discussion on extending AI-assisted programming capabilities to Apple’s Xcode for mobile software development. This paper also presents the challenges of and opportunities for incorporating NLP techniques with software naturalness, empowering developers with advanced coding assistance and streamlining the software development process.

Angiogenesis inhibitors have been adopted into the standard armamentarium of therapies for advanced-stage renal cell carcinomas (RCC), but more recently, combination regimens with immune checkpoint inhibitors have demonstrated better outcomes. Despite this, the majority of affected patients still eventually experience progressive disease due to therapeutic resistance mechanisms, and there remains a need to develop novel therapeutic strategies. This article will review the synergistic mechanisms behind angiogenesis and immunomodulation in the tumor microenvironment and discuss the pre-clinical and clinical evidence for both clear-cell and non-clear-cell RCC, exploring opportunities for future growth in this exciting area of drug development.

Background Doublet chemotherapy in combination with a biologic agent has been a standard of care in patients with metastatic colorectal cancer for over a decade. The evidence for a “lighter” treatment approach is limited to mono-chemotherapy plus bevacizumab in the RAS unselected population. Anti-EGFR antibodies have activity as monotherapy or in combination with chemotherapy in RAS wildtype metastatic colorectal cancer; however their role in first-line treatment in combination with 5-fluorouracil monotherapy or when given alone has not been well studied. MONARCC aims to investigate this approach in an elderly population. Methods/design MONARCC is a prospective, open-label, multicentre, non-comparative randomised phase II trial. Eligible patients aged ≥70 with unresectable metastatic, untreated, RAS / BRAF wildtype metastatic colorectal cancer will be randomised 1:1 to receive panitumumab alone or panitumumab plus infusional 5-fluorouracil. RAS and BRAF analyses will be performed in local laboratories. Comprehensive Health Assessment and Limited Health Assessments will be performed at baseline and at 16 weeks, respectively, to assess frailty. The Patient Symptom Questionnaire and Overall Treatment Utility are to be undertaken at different timepoints to assess the impact of treatment-related toxicities and quality of life. Treatment will be delivered every 2 weeks until disease progression, unacceptable toxicity (as determined by treating clinician or patient), delay of treatment of more than 6 weeks, or withdrawal of consent. The primary end point is 6-month progression-free survival in both arms. Secondary end points include overall survival, time to treatment failure, objective tumour response rate as defined by RECIST v1.1 and safety (adverse events). Tertiary and correlative endpoints include the feasibility and utility of a comprehensive geriatric assessment, quality of life and biological substudies. Discussion MONARCC investigates the activity and tolerability of first-line panitumumab-based treatments with a view to expand on current treatment options while maximising progression-free and overall survival and quality of life in molecularly selected elderly patients with metastatic colorectal cancer. Trial registration Australia New Zealand Clinical Trials Registry: ACTRN12618000233224 , prospectively registered 14 February 2018.

Private information retrieval scheme for coded data storage is considered in this paper. We focus on the case where the size of each data record is large and hence only the download cost (but not the upload cost for transmitting retrieval queries) is of interest. We prove that the tradeoff between storage cost and retrieval/download cost depends on the number of data records in the system. We also propose a fairly general class of linear storage codes and retrieval schemes and derive conditions under which our retrieval schemes are error-free and private. Tradeoffs between the storage cost and retrieval costs are also obtained. Finally, we consider special cases when the underlying storage code is based on an MDS code. Using our proposed method, we show that a randomly generated retrieval scheme is indeed very likely to be private and error-free.

Motivated by communication through a network employing linear network coding, capacities of linear operator channels (LOCs) with arbitrarily distributed transfer matrices over finite fields are studied. Both the Shannon capacity \\(C\\) and the subspace coding capacity \\(C_{\\text{SS}}\\) are analyzed. By establishing and comparing lower bounds on \\(C\\) and upper bounds on \\(C_{\\text{SS}}\\), various necessary conditions and sufficient conditions such that \\(C=C_{\\text{SS}}\\) are obtained. A new class of LOCs such that \\(C=C_{\\text{SS}}\\) is identified, which includes LOCs with uniform-given-rank transfer matrices as special cases. It is also demonstrated that \\(C_{\\text{SS}}\\) is strictly less than \\(C\\) for a broad class of LOCs. In general, an optimal subspace coding scheme is difficult to find because it requires to solve the maximization of a non-concave function. However, for a LOC with a unique subspace degradation, \\(C_{\\text{SS}}\\) can be obtained by solving a convex optimization problem over rank distribution. Classes of LOCs with a unique subspace degradation are characterized. Since LOCs with uniform-given-rank transfer matrices have unique subspace degradations, some existing results on LOCs with uniform-given-rank transfer matrices are explained from a more general way.

Shannon's fundamental bound for perfect secrecy says that the entropy of the secret message cannot be larger than the entropy of the secret key initially shared by the sender and the legitimate receiver. Massey gave an information theoretic proof of this result, however this proof does not require independence of the key and ciphertext. By further assuming independence, we obtain a tighter lower bound, namely that the key entropy is not less than the logarithm of the message sample size in any cipher achieving perfect secrecy, even if the source distribution is fixed. The same bound also applies to the entropy of the ciphertext. The bounds still hold if the secret message has been compressed before encryption. This paper also illustrates that the lower bound only gives the minimum size of the pre-shared secret key. When a cipher system is used multiple times, this is no longer a reasonable measure for the portion of key consumed in each round. Instead, this paper proposes and justifies a new measure for key consumption rate. The existence of a fundamental tradeoff between the expected key consumption and the number of channel uses for conveying a ciphertext is shown. Optimal and nearly optimal secure codes are designed.

Background Abundant, indirect epidemiological evidence indicates that influenza contributes to all-cause mortality and cardiovascular hospitalisations with studies showing increases in acute myocardial infarction (AMI) and death during the influenza season. Objective To investigate whether influenza is a significant and unrecognised underlying precipitant of AMI. Design Case-control study. Setting Tertiary referral hospital in Sydney, Australia, during 2008 to 2010. Patients Cases were inpatients with AMI and controls were outpatients without AMI at a hospital in Sydney, Australia. Main outcome measures Primary outcome was laboratory evidence of influenza. Secondary outcome was baseline self-reported acute respiratory tract infection. Results Of 559 participants, 34/275 (12.4%) cases and 19/284 (6.7%) controls had influenza (OR 1.97, 95% CI 1.09 to 3.54); half were vaccinated. None were recognised as having influenza during their clinical encounter. After adjustment, influenza infection was no longer a significant predictor of recent AMI. However, influenza vaccination was significantly protective (OR 0.55, 95% CI 0.35 to 0.85), with a vaccine effectiveness of 45% (95% CI 15% to 65%). Conclusions Recent influenza infection was an unrecognised comorbidity in almost 10% of hospital patients. Influenza did not predict AMI, but vaccination was significantly protective but underused. The potential population health impact of influenza vaccination, particularly in the age group 50–64 years, who are at risk for AMI but not targeted for vaccination, should be further explored. Our data should inform vaccination policy and cardiologists should be aware of missed opportunities to vaccinate individuals with ischaemic heart disease against influenza.

BackgroundThe use of immune checkpoint inhibitors (ICIs) against programmed cell death protein -1 (PD-1), its ligand (PD-L1) and cytotoxic T- lymphocyte associated protein 4 (CTLA4) have been increasing. Immune induced myocarditis, myositis and myasthenia gravis are rare but potentially severe complications from these agents. Here we report 3 cases of ICI induced myocarditis, myositis, myasthenia gravis and transaminitis as a cluster, and highlights early diagnosis, prompt initiation of steroid sparing immunosuppressive therapy and multidisciplinary management.MethodsThree patients received anti-PD-1 ICIs developed cardiac, neuromuscular complications and transaminitis within 4 weeks after initiation. Clinical data were retrospectively reviewed from medical records.ResultsAll patients had elevated cardiac enzymes, developed complete heart block and underwent coronary catheterisation and pacemaker insertion. All patients developed myositis and myasthenia gravis (table 1) and were managed by multi-disciplinary team involving oncology, cardiology and neurology. Single-fibre electromyography was performed to confirm presence of myositis. One of three patients had positive acetylcholinesterase antibody, anti- muscle specific kinase antibody was negative in all cases. All patients developed grade 2–3 transaminitis with normal bilirubin. All patients received high-dose steroids. Steroid sparing therapy including intravenous immunoglobulin and mycophenolate mofetil were used early in 2 cases and was associated with rapid recovery of toxicities.Abstract 292 Table 1Patient characteristics, management and outcome of ir-AEsConclusionsICI induced myocarditis can be associated with myositis, myasthenia gravis and transaminitis. A high index of suspicion, comprehensive investigations and early involvement of multi-disciplinary teams are key to early accurate diagnosis. In steroid refractory cases, we propose early initiation of steroid sparing immunosuppressive therapy after 3 days.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

Motivated by linear network coding, communication channels perform linear operation over finite fields, namely linear operator channels (LOCs), are studied in this paper. For such a channel, its output vector is a linear transform of its input vector, and the transformation matrix is randomly and independently generated. The transformation matrix is assumed to remain constant for every T input vectors and to be unknown to both the transmitter and the receiver. There are NO constraints on the distribution of the transformation matrix and the field size. Specifically, the optimality of subspace coding over LOCs is investigated. A lower bound on the maximum achievable rate of subspace coding is obtained and it is shown to be tight for some cases. The maximum achievable rate of constant-dimensional subspace coding is characterized and the loss of rate incurred by using constant-dimensional subspace coding is insignificant. The maximum achievable rate of channel training is close to the lower bound on the maximum achievable rate of subspace coding. Two coding approaches based on channel training are proposed and their performances are evaluated. Our first approach makes use of rank-metric codes and its optimality depends on the existence of maximum rank distance codes. Our second approach applies linear coding and it can achieve the maximum achievable rate of channel training. Our code designs require only the knowledge of the expectation of the rank of the transformation matrix. The second scheme can also be realized ratelessly without a priori knowledge of the channel statistics.