A Total Randomized SLP-Preserving Technique with Improved Privacy and Lifetime in WSNs for IoT and the Impact of Radio Range on SLP

Enhanced source location privacy and prolonged network lifetime are imperative for WSNs-the skin of IoT. To address these issues, a novel technique named source location privacy with enhanced privacy and network lifetime (SLP-E) is proposed. It employs a reverse random walk followed by a walk on annular rings, to create divergent routing paths in the network, and finally, min-hop routing together with the walk on dynamic rings to send the packets to the base station (BS). The existing random walk-based SLP approaches have either focused on enhancing only privacy at the cost of network lifetime (NLT) or have aimed at improving the amount of privacy without degrading the network lifetime performance. Unlike these schemes, the objectives of the proposed work are to simultaneously improve the safety period and network lifetime along with achieving uniform privacy. This combination of improvements has not been considered so far in a single SLP random walk-based scheme. Additionally, this study investigates for the first time the impact of the sensors' radio range on both privacy strength and network lifetime metrics in the context of SLP within WSNs. The performance measurements conducted using the proposed analytical models and the simulation results indicate an improvement in the safety period and network lifespan. The safety period in SLP-E increased by 26.5%, 97%, 123%, and 15.7% when compared with SLP-R, SRR, PRLPRW, and PSSLP techniques, respectively. Similarly, the network lifetime of SLP-E increased by 17.36%, 0.2%, 83.41%, and 13.42% when compared with SLP-R, SRR, PRLPRW, and PSSLP techniques, respectively. No matter where a source node is located within a network, the SLP-E provides uniform and improved privacy and network lifetime. Further, the simulation results demonstrate that the sensors' radio range has an impact on the safety period, capture ratio, and the network lifetime.

Dysphagia and pill swallowing in HIV/AIDS in South Africa: Results of a scoping review

BACKGROUND

 South Africa has the highest prevalence of human immunodeficiency virus (HIV) worldwide. Highly active antiretroviral therapy (HAART) is expected to improve the quality of life for these individuals but requires long-term medication intake. Poor pill adherence and related dysphagia are undocumented for individuals on HAART regimens living in South Africa.

AIM

 To conduct a scoping review describing the presentation of pill swallowing difficulties and dysphagia experiences of individuals with HIV and acquired immunodeficiency syndrome (AIDS) in South Africa.

METHOD

 This review describes the presentation of pill swallowing difficulties and dysphagia experiences of individuals with HIV and AIDS in South Africa using a modified version of the Arksey and O'Malley framework. Five search engines targeting published journal articles were reviewed. Two hundred and twenty-seven articles were retrieved; however, following the exclusion criteria based on PICO, only three articles were included. Qualitative analysis was completed.

RESULTS

 The reviewed articles identified swallowing difficulties that adults with HIV and AIDS experienced and confirmed non-adherence to medical regimens. Barriers and facilitators of pill swallowing with dysphagia due to the side-effects of the pill itself were documented with physical properties of the pill not influencing adherence.

CONCLUSION

 The speech-language pathologists (SLPs) role with individuals with HIV/AIDS to facilitate improved pill adherence was lacking with limited research on the management of swallowing difficulties in this population. The review identified dysphagia and pill adherence management by the SLP in South Africa as caveats for further research.Contribution: Speech-language pathologists must monitor swallowing during mealtimes as well as pill swallowing in individuals with HIV/AIDS due to the compromise of their oral health and oral structures. Speech-language pathologists therefore have to advocate for their role in the team managing this population of patients. Their involvement may reduce the risk of nutritional compromise as well as patient non-compliance with medication stemming from pain and inability to swallow solid oral dosage forms of medication.

Innovation through participatory design: Collaborative qualitative methods in the development of speech-language pathology technology

Speech-language pathologists have embraced many aspects of technology in their practice, from telehealth to tablet device applications (apps) that support intervention practice. In this article, we consider the design, development, and implementation of technology. We discuss how some processes of technology development in Speech-language pathology (SLP) tend to follow research pathways which centre clinicians and researchers as designers of the intervention. This approach side-lines user involvement. We propose that a Participatory Design framework is a suitable way to reconceptualise design and development of these technological innovations in a client-centred way. Further, we explore how Participatory Design approaches utilise methods from and have much in common with qualitative research. We explore this overlap and propose that technology design teams take up the challenge of innovation in technology by engaging in a participatory rather than clinician-driven process for future technology design. Implications for both research and clinical practice are explored.

Combination of Photodynamic Therapy and Therapeutic Vaccination

Tumor ablation by photodynamic therapy (PDT) results in a strong reduction in tumor mass and can lead to improved recognition of tumor cells by the immune system. This supports combinations of PDT and immunotherapy for the treatment of advanced tumors. Therapeutic vaccination is a tumor-specific type of cancer immunotherapy that aims to directly strengthen the immune response against tumor antigens. In this chapter, we describe the combination of PDT and therapeutic vaccination using a peptide tumor antigen vaccine.

Using kinetic Monte Carlo simulations to design efficient magnetic nanoparticles for clinical hyperthermia

PURPOSE

The purpose of this study was to identify the properties of magnetite nanoparticles that deliver optimal heating efficiency, predict the geometrical characteristics to get these target properties, and determine the concentrations of nanoparticles required to optimize thermotherapy.

METHODS

Kinetic Monte Carlo simulations were employed to identify the properties of magnetic nanoparticles that deliver high Specific Absorption Rate (SAR) values. Optimal volumes were determined for anisotropies ranging between 11 and 40 kJ/m³ under clinically relevant magnetic field conditions. Atomistic spin simulations were employed to determine the aspect ratios of ellipsoidal magnetite nanoparticles that deliver the target properties. A numerical model was developed using the extended cardiac-torso (XCAT) phantom to simulate low-field (4 kA/m) and high-field (18 kA/m) prostate cancer thermotherapy. A stationary optimization study exploiting the Method of Moving Asymptotes (MMA) was carried out to calculate the concentration fields that deliver homogenous temperature distributions within target thermotherapy range constrained by the optimization objective function. A time-dependent study was used to compute the thermal dose of a 30-min session.

RESULTS

Prolate ellipsoidal magnetite nanoparticles with a volume of 3922 ± 35 nm³ and aspect ratio of 1.56, which yields an effective anisotropy of 20 kJ/m³ , constituted the optimal design at current maximum clinical field properties (H₀   = 18 kA/m, f = 100 kHz), with SAR = 342.0 ± 2.7 W/g, while nanoparticles with a volume of 4147 ± 36 nm³ , aspect ratio of 1.29, and effective anisotropy 11 kJ/m³ were optimal for low-field applications (H₀   = 4 kA/m, f = 100 kHz), with SAR = 50.2 ± 0.5 W/g. The average concentration of 3.86 ± 0.10 and 0.57 ± 0.01 mg/cm³ at 4 and 18 kA/m, respectively, were sufficient to reach therapeutic temperatures of 42-44°C throughout the prostate volume. The thermal dose delivered during a 30-min session exceeded 5.8 Cumulative Equivalent Minutes at 43°C within 90% of the prostate volume (CEM43T₉₀ ).

CONCLUSION

The optimal properties and design specifications of magnetite nanoparticles vary with magnetic field properties. Application-specific magnetic nanoparticles or nanoparticles that are optimized at low fields are indicated for optimal thermal dose delivery at low concentrations.

Mass violence planned as ultimate leisure experience? Four diverse cases

As part of a larger project on contextual factors of mass murder, this paper identifies and discusses four cases that quite clearly suggest, based on the content of perpetrators' personal communications and/or reports from those who knew them, that the perpetrators purposely planned and experienced their attacks as desired leisure experience. Leisure science, while consistent with the multidisciplinary roots of forensic behavioral science, has not yet been applied to better understand cases of mass violence. Together with traditional forensic behavioral science approaches, leisure theory may produce insights in cases of mass violence that are uncoerced, largely intrinsically motivated, and committed for personal enjoyment.

Fast and Space-Efficient Construction of AVL Grammars from the LZ77 Parsing

Grammar compression is, next to Lempel-Ziv (LZ77) and run-length Burrows-Wheeler transform (RLBWT), one of the most flexible approaches to representing and processing highly compressible strings. The main idea is to represent a text as a context-free grammar whose language is precisely the input string. This is called a straight-line grammar (SLG). An AVL grammar, proposed by Rytter [Theor. Comput. Sci., 2003] is a type of SLG that additionally satisfies the AVL property: the heights of parse trees for children of every nonterminal differ by at most one. In contrast to other SLG constructions, AVL grammars can be constructed from the LZ77 parsing in compressed time: 𝓞 ( z log n ) where z is the size of the LZ77 parsing and n is the length of the input text. Despite these advantages, AVL grammars are thought to be too large to be practical. We present a new technique for rapidly constructing a small AVL grammar from an LZ77 or LZ77-like parse. Our algorithm produces grammars that are always at least five times smaller than those produced by the original algorithm, and usually not more than double the size of grammars produced by the practical Re-Pair compressor [Larsson and Moffat, Proc. IEEE, 2000]. Our algorithm also achieves low peak RAM usage. By combining this algorithm with recent advances in approximating the LZ77 parsing, we show that our method has the potential to construct a run-length BWT in about one third of the time and peak RAM required by other approaches. Overall, we show that AVL grammars are surprisingly practical, opening the door to much faster construction of key compressed data structures.

Patterns and predictors of referrals to allied health services for individuals with Parkinson's disease: A Parkinson's foundation (PF) QII study

INTRODUCTION

Rehabilitation therapies are critical for optimizing quality-of-life and daily functions for individuals living with Parkinson's disease (PD). Thus, understanding the patterns of and under what conditions physicians make rehabilitation referrals is important for optimizing care.

METHOD

We analyzed data from 5020 participants (4 countries) collected from 1/3/2016 to 4/20/2018 as part of the Parkinson's Foundation Quality Improvement Initiative (PF QII). Data were analyzed for single discipline and multidiscipline referrals to speech language pathology (SLP), physical therapy (PT), and occupational therapy (OT). Group comparisons (referred vs. not-referred) and regression procedures were implemented to determine demographic and clinical variables that were associated with an increased likelihood of rehabilitation referral.

RESULTS

35.3% of participants were referred to rehabilitation services. Of these, 25.1% received a multidiscipline referral. There was a statistically significant effect of disease stage on both single discipline (χ²(2) = 45.1, p < 0.0001) and multidiscipline (χ²(2) = 74.2, p < 0.0001) referrals, with higher rates in later stages. Referred vs. not-referred participants differed significantly on a number of variables; however, only falls in the 6-months prior, advanced- and moderate-stage disease, older age, hospital admissions, and higher caregiver burden were associated with an increased likelihood of rehabilitation referral (adjusted odds ratios ≥ 1, Range = 1.08 to 1.62).

CONCLUSIONS

Despite evidence supporting multidiscipline and proactive rehabilitation in PD, the majority of referrals were made to a single service and may be reactions to falls or advancing disease. Data suggest there may be missed opportunities for optimizing care through proactive rehabilitation interventions.

ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data

Heterogeneous mental disorders such as Autism Spectrum Disorder (ASD) are notoriously difficult to diagnose, especially in children. The current psychiatric diagnostic process is based purely on the behavioral observation of symptomology (DSM-5/ICD-10) and may be prone to misdiagnosis. In order to move the field toward more quantitative diagnosis, we need advanced and scalable machine learning infrastructure that will allow us to identify reliable biomarkers of mental health disorders. In this paper, we propose a framework called ASD-DiagNet for classifying subjects with ASD from healthy subjects by using only fMRI data. We designed and implemented a joint learning procedure using an autoencoder and a single layer perceptron (SLP) which results in improved quality of extracted features and optimized parameters for the model. Further, we designed and implemented a data augmentation strategy, based on linear interpolation on available feature vectors, that allows us to produce synthetic datasets needed for training of machine learning models. The proposed approach is evaluated on a public dataset provided by Autism Brain Imaging Data Exchange including 1, 035 subjects coming from 17 different brain imaging centers. Our machine learning model outperforms other state of the art methods from 10 imaging centers with increase in classification accuracy up to 28% with maximum accuracy of 82%. The machine learning technique presented in this paper, in addition to yielding better quality, gives enormous advantages in terms of execution time (40 min vs. 7 h on other methods). The implemented code is available as GPL license on GitHub portal of our lab (https://github.com/pcdslab/ASD-DiagNet).

Evaluation of excitation schemes for indirect detection of 14N via solid-state HMQC NMR experiments

It has previously been shown that ¹⁴N NMR spectra can be reliably obtained through indirect detection via HMQC experiments. This method exploits the transfer of coherence between single-(SQ) or double-quantum (DQ) ¹⁴N coherences, and SQ coherences of a suitable spin-1/2 'spy' nucleus, e.g., ¹H. It must be noted that SQ-SQ methods require a carefully optimized setup to minimize the broadening related to the first-order quadrupole interaction (i.e., an extremely well-adjusted magic angle and a highly stable spinning speed), whereas DQ-SQ ones do not. In this work, the efficiencies of four ¹⁴N excitation schemes (DANTE, XiX, Hard Pulse (HP), and Selective Long Pulse (SLP)) are compared using J-HMQC based numerical simulations and either SQ-SQ or DQ-SQ ¹H-{¹⁴N} D-HMQC experiments on l-histidine HCl and N-acetyl-l-valine at 18.8 T and 62.5 kHz MAS. The results demonstrate that both DANTE and SLP provide a more efficient ¹⁴N excitation profile than XiX and HP. Furthermore, it is shown that the SLP scheme: (i) is efficient over a large range of quadrupole interaction, (ii) is highly robust to offset and rf-pulse length and amplitude, and (iii) is very simple to set up. These factors make SLP ideally suited to widespread, non-specialist use in solid-state NMR analyses of nitrogen-containing materials.

Diagnostic accuracy of stress perfusion CMR in comparison with quantitative coronary angiography: fully quantitative, semiquantitative, and qualitative assessment

OBJECTIVES

This study's primary objective was to determine the sensitivity, specificity, and accuracy of fully quantitative stress perfusion cardiac magnetic resonance (CMR) versus a reference standard of quantitative coronary angiography. We hypothesized that fully quantitative analysis of stress perfusion CMR would have high diagnostic accuracy for identifying significant coronary artery stenosis and exceed the accuracy of semiquantitative measures of perfusion and qualitative interpretation.

BACKGROUND

Relatively few studies apply fully quantitative CMR perfusion measures to patients with coronary disease and comparisons to semiquantitative and qualitative methods are limited.

METHODS

Dual bolus dipyridamole stress perfusion CMR exams were performed in 67 patients with clinical indications for assessment of myocardial ischemia. Stress perfusion images alone were analyzed with a fully quantitative perfusion (QP) method and 3 semiquantitative methods including contrast enhancement ratio, upslope index, and upslope integral. Comprehensive exams (cine imaging, stress/rest perfusion, late gadolinium enhancement) were analyzed qualitatively with 2 methods including the Duke algorithm and standard clinical interpretation. A 70% or greater stenosis by quantitative coronary angiography was considered abnormal.

RESULTS

The optimum diagnostic threshold for QP determined by receiver-operating characteristic curve occurred when endocardial flow decreased to <50% of mean epicardial flow, which yielded a sensitivity of 87% and specificity of 93%. The area under the curve for QP was 92%, which was superior to semiquantitative methods: contrast enhancement ratio: 78%; upslope index: 82%; and upslope integral: 75% (p = 0.011, p = 0.019, p = 0.004 vs. QP, respectively). Area under the curve for QP was also superior to qualitative methods: Duke algorithm: 70%; and clinical interpretation: 78% (p < 0.001 and p < 0.001 vs. QP, respectively).

CONCLUSIONS

Fully quantitative stress perfusion CMR has high diagnostic accuracy for detecting obstructive coronary artery disease. QP outperforms semiquantitative measures of perfusion and qualitative methods that incorporate a combination of cine, perfusion, and late gadolinium enhancement imaging. These findings suggest a potential clinical role for quantitative stress perfusion CMR.

Two in one: improving synthetic long peptide vaccines by combining antigen and adjuvant in one molecule

Aiming to increase the potency of synthetic long peptide (SLP)-based cancer vaccines, the Toll-like receptor 2 (TLR2) ligand Pam₃CSK₄ was conjugated in a chemically defined fashion to SLPs harbouring both cytotoxic T lymphocyte (CTL) and T helper epitopes. We recently showed that these SLP-conjugates induce strong antitumor immunity in murine cancer models.

Comparison of the nerve fiber layer of type 2 diabetic patients without glaucoma with normal subjects of the same age and sex

BACKGROUND

The retinal nerve fiber layer (RNFL) thickness in patients with diabetes mellitus type 2 was compared to normal subjects of similar age and sex, having first excluded any risk factors for glaucoma. The correlation between the RNFL thickness and the severity of diabetic retinopathy was investigated at its primary stages and with other ocular and diabetic parameters.

METHODS

A prospective, case series study was carried out. Twenty-seven diabetic patients without diabetic retinopathy, 24 diabetic patients with mild retinopathy, and 25 normal, age-matched subjects underwent a complete ophthalmological examination and imaging with scanning laser polarimetry for the evaluation of the RNFL. Multivariate analysis was applied in order to investigate the correlation between RNFL and diabetic parameters, such as age, duration of diabetes, insulin therapy, levels of glycosylated hemoglobin; and ocular parameters, such as cup to disc ratio, levels of normal intraocular pressure, and central corneal thickness.

RESULTS

The mean inferior average of RNFL and the temporal-superior-nasal-inferior-temporal standard deviation were statistically significantly lower in both diabetic groups, and the nerve fiber index was higher (P=0.04) compared to the normal group. There was no statistically significant difference between the diabetic groups. The factor analysis showed no significant correlation between the RNFL and the previously mentioned diabetic and ocular parameters.

CONCLUSION

The existence of diabetes should be seriously considered in evaluating the results of scanning laser polarimetry. Multivariate analysis for RNFL was used for the first time.

Specialized early treatment for persons with disorders of consciousness: program components and outcomes

OBJECTIVES

To describe a specialized early treatment program for persons with disorders of consciousness (DOC) that includes family education; to identify rates of secondary conditions, imaging used, and selected interventions; and to evaluate outcomes.

DESIGN

A single-center, retrospective, pre-post design using electronic medical record data.

SETTING

A Commission on Accreditation of Rehabilitation Facilities-accredited, long-term acute care hospital that provides acute medical and inpatient rehabilitation levels of care for people with catastrophic injuries.

PARTICIPANTS

Persons (N=210) aged 14 to 69 years with DOC of primarily traumatic etiology admitted at a mean ± SD of 41.0 ± 27.2 days postinjury; 2% were in coma, 41% were in the vegetative state, and 57% were in the minimally conscious state.

INTERVENTIONS

An acute medical level of care with ≥90 minutes of daily interdisciplinary rehabilitation and didactic and hands-on caretaking education for families.

MAIN OUTCOME MEASURES

Coma Recovery Scale-Revised, Modified Ashworth Scale, and discharge disposition.

RESULTS

Program admission medical acuity included dysautonomia (15%), airway modifications (79%), infections (eg, pneumonia, 16%; urinary tract infection, 14%; blood, 11%), deep vein thrombosis (17%), pressure ulcers (14%), and marked hypertonia (30% in each limb). There were 168 program interruptions (ie, 139 surgeries, 29 nonsurgical intensive care unit transfers). Mean length of stay ± SD was 39.1 ± 29.4 days (range, 6-204d). Patients showed improved consciousness and respiratory function and reduced presence or severity of pressure ulcers and upper extremity hypertonia. At discharge, 54% showed sufficient emergence from a minimally conscious state to transition to mainstream inpatient rehabilitation, and 29% did not emerge but were discharged home to family with ongoing programmatic support; only 13% did not emerge and were institutionalized.

CONCLUSIONS

Persons with DOC resulting primarily from a traumatic etiology who receive specialized early treatment that includes acute medical care and ≥90 minutes of daily rehabilitation are likely to show improved consciousness and body function; more than half may transition to mainstream inpatient rehabilitation. Families who receive comprehensive education and hands-on training with ongoing follow-up support may be twice as likely to provide care for medically stable persons with DOC in their homes versus nursing facility placement.