by Sheri Tran  and Mark M Fuster

Received: 16 July 2017;  Published: 12 September 2017;  doi: 10.21926/obm.transplant.1703004

The risk for developing a variety of malignancies is significantly elevated in the setting of lung transplantation. Malignancy remains among the three major causes of death in post-transplant recipients, and the relatively high risk of cancer development as well as metastatic aggression pose special threats to this population due to the need for continued immunosuppression. A variety of risks such as tobacco use and inflammatory lung diseases that led to the lung pathology prompting lung transplantation, in additio [...]

by In Lam  , Irina Gutman  , Ashley Feist  and Mark Mariski

Received: 10 March 2017;  Published: 22 June 2017;  doi: 10.21926/obm.transplant.1701003

After lung transplant, infection is a leading contributor to morbidity and mortality, and hypogammaglobulinemia (HGG) may be an important risk factor for many of these infections. Some reports suggest that HGG not only increases the risk of various infections, but also worsens survival. The incidence of HGG has been shown to increase after lung transplant, and may be as high as 70%. In order to mitigate this risk, intravenous immunoglobulin G (IVIG) replacement for the treatment of HGG has been utilized. However, t [...]

by Gerald P. Morris

Received: 22 February 2019;  Published: 11 April 2017;  doi: 10.21926/obm.transplant.1701002

(1) Background: Lung transplantation is an increasingly utilized treatment for end-stage lung disease. Scarcity of organ donors limiting transplantation underscores the importance of optimal histocompatibility testing approaches to facilitate organ allocation and avoid immunologic rejection. Significant data has emerged over the past decade to define the role of alloantibodies against HLA in the pathogenesis of post-lung transplant complications. (2) Methods: Medical literature from 1996–2016 related to search term [...]

by Pål Dag Line

Received: 07 April 2017;  Published: 11 April 2017;  doi: 10.21926/obm.transplant.1701001

by Máximo Augusto Poggio Sendra  and A. Guillermo Bracamonte

Received: 02 February 2026;  Published: 25 August 2026;  doi: 10.21926/rpse.2603018

In this commentary article, the discussion is about how optics from tiny-sized structures formed by a few atoms and molecules was the beginning of higher-sized effects and phenomena forming part of micro- and macro-sized materials with targeted functions, smart responses, and instrumentation of varied dimensions used daily for well-being. In this manner, the optical properties developed by varied molecules with particular capabilities to absorb and filter intervals of wavelengths and related colours could participa [...]

by Kevin Curran  , Jack Kyle  and Lovepreet Singh

Received: 04 April 2026;  Published: 19 August 2026;  doi: 10.21926/rpse.2603017

The Internet of Things (IoT) is transforming industries and daily life by connecting billions of devices, enabling smart homes, cities and industrial systems. This rapid expansion, however, introduces significant cybersecurity vulnerabilities, leaving IoT systems increasingly exposed to both established and emerging attack techniques. This paper presents a structured critical review of IoT cybersecurity, distinguished from prior general surveys by three contributions: first, a cross-layer mapping of named, dated ca [...]

by Emmanuel Ugochukwu Anaso

Received: 16 February 2026;  Published: 30 July 2026;  doi: 10.21926/rpse.2603016

Sheep production systems in sub-Saharan Africa are largely constrained by seasonal fluctuations in feed availability and persistent shortages in both the quantity and quality of forages throughout the year. These limitations adversely affect growth performance and reproductive efficiency in sheep. In addition, the escalating cost of conventional feed ingredients used in ration formulation has intensified the search for alternative, affordable, and locally available feed resources that do not compete directly with h [...]

by Moa’ath Sa’ad Al-A’athal  and Qasem Abu Al-Haija

Received: 28 March 2026;  Published: 20 July 2026;  doi: 10.21926/rpse.2603015

The increasing scale, speed, and sophistication of cyberattacks have rendered traditional rule-based intrusion detection systems (IDS) insufficient for modern network environments. While machine learning (ML)-based IDSs have significantly improved detection capabilities, their black-box nature limits trust, interpretability, and practical deployment in real-world security operations. To address this challenge, this paper proposes an explainable machine learning framework for network intrusion detection using the CI [...]

by Ankit Kumar Singh  , Aastha Singh  , Avanish Kant Agnihotri  , Amit Trivedi  and Mohd Nadeem

Received: 12 March 2026;  Published: 01 July 2026;  doi: 10.21926/rpse.2603014

The advent of cloud computing, the Internet of Things (IoT), and digital services has led to an increase in the number and complexity of cyberattacks. The intrusion detection methods currently used, based on machine learning and artificial intelligence, include SVM, random forest, deep learning, convolutional neural networks, and LSTM. These methods are more advanced than the signature method since they are more efficient. However, despite these advancements, several issues with intrusion detection systems remain. [...]

by Kadir Aydın  and Çağrı Ün

Received: 11 May 2026;  Published: 01 July 2026;  doi: 10.21926/rpse.2603013

Thermal runaway in lithium-ion batteries (LIBs) is an escalating fire-safety problem in electric vehicles and battery energy-storage systems (BESS), and conventional water-based suppression has repeatedly been shown to delay propagation without preventing pack destruction or re-ignition. Solid, electrically non-conductive cooling agents are a promising but under-characterized alternative. This study addresses the absence of comparative, in-pack data on boron-based salt-hydrate cooling powders. Eight propane-burner [...]