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Physically or externally stimulated nanostructures often employ multimodality and show encouraging results at preclinical stage in cancer therapy. Specially designed smart nanostructures such as hybrid nanostructures are responsive to external physical stimuli such as light, magnetic field, electric, ultrasound, radio frequency, X-ray, etc. These physically responsive nanostructures have been widely explored as nonconventional innovative “nanotheranostics” in cancer therapies. Physically stimulated (particularly magnetic and light) nanotheranostics provide a unique combination of important properties to address key challenges in modern cancer therapy: (i) an active tumor targeting mechanism of therapeutic drugs driven by a physical force rather than passive antibody matching, (ii) an externally/remotely controlled drugs on-demand release mechanism, and (iii) a capability for advanced image guided tumor therapy and therapy monitoring. Although primarily addressed to the scientific community, this review offers valuable and accessible information for a wide range of readers interested in the current technological progress with direct relevance to the physics, chemistry, biomedical field, and theranostics. We herein cover magnetic and light-triggered modalities currently being developed for nonconventional cancer treatments. The physical basis of each modality is explained; so readers with a physics or, materials science background can easily grasp new developments in this field.

Opiate overdose is a significant cause of mortality among injection drug users (IDUs) in the United States (US). Opiate overdose can be reversed by administering naloxone, an opiate antagonist. Among IDUs, prevalence of witnessing overdose events is high, and the provision of take-home naloxone to IDUs can be an important intervention to reduce the number of overdose fatalities. The Drug Overdose Prevention and Education (DOPE) Project was the first naloxone prescription program (NPP) established in partnership with a county health department (San Francisco Department of Public Health), and is one of the longest running NPPs in the USA. From September 2003 to December 2009, 1,942 individuals were trained and prescribed naloxone through the DOPE Project, of whom 24% returned to receive a naloxone refill, and 11% reported using naloxone during an overdose event. Of 399 overdose events where naloxone was used, participants reported that 89% were reversed. In addition, 83% of participants who reported overdose reversal attributed the reversal to their administration of naloxone, and fewer than 1% reported serious adverse effects. Findings from the DOPE Project add to a growing body of research that suggests that IDUs at high risk of witnessing overdose events are willing to be trained on overdose response strategies and use take-home naloxone during overdose events to prevent deaths.

Opiate overdose is a significant cause of mortality among injection drug users (IDUs) in the United States (US). Opiate overdose can be reversed by administering naloxone, an opiate antagonist. Among IDUs, prevalence of witnessing overdose events is high, and the provision of take-home naloxone to IDUs can be an important intervention to reduce the number of overdose fatalities. The Drug Overdose Prevention and Education (DOPE) Project was the first naloxone prescription program (NPP) established in partnership with a county health department (San Francisco Department of Public Health), and is one of the longest running NPPs in the USA. From September 2003 to December 2009, 1,942 individuals were trained and prescribed naloxone through the DOPE Project, of whom 24% returned to receive a naloxone refill, and 11% reported using naloxone during an overdose event. Of 399 overdose events where naloxone was used, participants reported that 89% were reversed. In addition, 83% of participants who reported overdose reversal attributed the reversal to their administration of naloxone, and fewer than 1% reported serious adverse effects. Findings from the DOPE Project add to a growing body of research that suggests that IDUs at high risk of witnessing overdose events are willing to be trained on overdose response strategies and use take-home naloxone during overdose events to prevent deaths.

The Broadcast Incremental Power (BIP) algorithm is the most frequently cited method for the minimum energy broadcast routing problem. A recent survey concluded that BIP has O(|V|(3)) time complexity, and that its approximation ratio is at least 4.33. We strengthen these results to O(|V|(2)) and 4.598, respectively., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan , New results on the time complexity and approximation ratio of the Broadcast Incremental Power algorithm, 2009, INFORMATION PROCESSING LETTERS, (109), 12, 615-619. http://dx.doi.org/10.1016/j.ipl.2009.02.012 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

Local search methods are often used to reduce the power consumption of broadcast routing in wireless networks. For a classic method, sweep, the best available time complexity result is O(vertical bar V vertical bar(4)). We present an O(vertical bar V vertical bar(2))-time method, which exhaustively removes unnecessary transmissions yielding a solution comparable to that of sweep., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan, A fast local search method for minimum energy broadcast in wireless ad hoc networks, 2009, OPERATIONS RESEARCH LETTERS, (37), 2, 75-79. http://dx.doi.org/10.1016/j.orl.2009.01.004 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

The Broadcast Incremental Power (BIP) algorithm is the most frequently cited method for the minimum energy broadcast routing problem. A recent survey concluded that BIP has O(|V|(3)) time complexity, and that its approximation ratio is at least 4.33. We strengthen these results to O(|V|(2)) and 4.598, respectively., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan , New results on the time complexity and approximation ratio of the Broadcast Incremental Power algorithm, 2009, INFORMATION PROCESSING LETTERS, (109), 12, 615-619. http://dx.doi.org/10.1016/j.ipl.2009.02.012 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

Local search methods are often used to reduce the power consumption of broadcast routing in wireless networks. For a classic method, sweep, the best available time complexity result is O(vertical bar V vertical bar(4)). We present an O(vertical bar V vertical bar(2))-time method, which exhaustively removes unnecessary transmissions yielding a solution comparable to that of sweep., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan, A fast local search method for minimum energy broadcast in wireless ad hoc networks, 2009, OPERATIONS RESEARCH LETTERS, (37), 2, 75-79. http://dx.doi.org/10.1016/j.orl.2009.01.004 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

Local search methods are often used to reduce the power consumption of broadcast routing in wireless networks. For a classic method, sweep, the best available time complexity result is O(vertical bar V vertical bar(4)). We present an O(vertical bar V vertical bar(2))-time method, which exhaustively removes unnecessary transmissions yielding a solution comparable to that of sweep., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan, A fast local search method for minimum energy broadcast in wireless ad hoc networks, 2009, OPERATIONS RESEARCH LETTERS, (37), 2, 75-79. http://dx.doi.org/10.1016/j.orl.2009.01.004 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

The Broadcast Incremental Power (BIP) algorithm is the most frequently cited method for the minimum energy broadcast routing problem. A recent survey concluded that BIP has O(|V|(3)) time complexity, and that its approximation ratio is at least 4.33. We strengthen these results to O(|V|(2)) and 4.598, respectively., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan , New results on the time complexity and approximation ratio of the Broadcast Incremental Power algorithm, 2009, INFORMATION PROCESSING LETTERS, (109), 12, 615-619. http://dx.doi.org/10.1016/j.ipl.2009.02.012 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

The Broadcast Incremental Power (BIP) algorithm is the most frequently cited method for the minimum energy broadcast routing problem. A recent survey concluded that BIP has O(|V|(3)) time complexity, and that its approximation ratio is at least 4.33. We strengthen these results to O(|V|(2)) and 4.598, respectively., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan , New results on the time complexity and approximation ratio of the Broadcast Incremental Power algorithm, 2009, INFORMATION PROCESSING LETTERS, (109), 12, 615-619. http://dx.doi.org/10.1016/j.ipl.2009.02.012 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

Local search methods are often used to reduce the power consumption of broadcast routing in wireless networks. For a classic method, sweep, the best available time complexity result is O(vertical bar V vertical bar(4)). We present an O(vertical bar V vertical bar(2))-time method, which exhaustively removes unnecessary transmissions yielding a solution comparable to that of sweep., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan, A fast local search method for minimum energy broadcast in wireless ad hoc networks, 2009, OPERATIONS RESEARCH LETTERS, (37), 2, 75-79. http://dx.doi.org/10.1016/j.orl.2009.01.004 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

The Broadcast Incremental Power (BIP) algorithm is the most frequently cited method for the minimum energy broadcast routing problem. A recent survey concluded that BIP has O(|V|(3)) time complexity, and that its approximation ratio is at least 4.33. We strengthen these results to O(|V|(2)) and 4.598, respectively., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan , New results on the time complexity and approximation ratio of the Broadcast Incremental Power algorithm, 2009, INFORMATION PROCESSING LETTERS, (109), 12, 615-619. http://dx.doi.org/10.1016/j.ipl.2009.02.012 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

Local search methods are often used to reduce the power consumption of broadcast routing in wireless networks. For a classic method, sweep, the best available time complexity result is O(vertical bar V vertical bar(4)). We present an O(vertical bar V vertical bar(2))-time method, which exhaustively removes unnecessary transmissions yielding a solution comparable to that of sweep., Original Publication: Joanna Bauer, Dag Haugland and Di Yuan, A fast local search method for minimum energy broadcast in wireless ad hoc networks, 2009, OPERATIONS RESEARCH LETTERS, (37), 2, 75-79. http://dx.doi.org/10.1016/j.orl.2009.01.004 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com

Both integer programming models and heuristic algorithms have been proposed for finding minimum-energy broadcast and multicast trees in wireless ad hoc networks. Among heuristic algorithms, the broadcast/multicast incremental power (BIP/MIP) algorithm is most known. The theoretical performance of BIP/MIP has been quantified in several studies. To assess the empirical performance of BIP/MIP and other heuristic algorithms, it is necessary to compute an optimal tree or a very good lower bound of the optimum. In this paper, we present an integer programming approach as well as improved heuristic algorithms. Our integer programming approach comprises a novel integer model and a relaxation scheme. Unlike previously proposed models, the continuous relaxation of our model leads to a very sharp lower bound of the optimum. Our relaxation scheme allows for performance evaluation of heuristics without having to compute optimal trees. Our contributions to heuristic algorithms consist of the power-improving algorithm successive power adjustment (SPA), and improved time complexity of some previously suggested algorithms. We report extensive numerical experiments. Algorithm SPA finds better solutions in comparison to a host of other algorithms. Moreover, the integer programming approach shows that trees found by algorithm SPA are optimal or near-optimal., Original publication: Di Yuan, Joanna Bauer and Dag Haugland, Minimum-Energy Broadcast and Multicast in Wireless Networks: An Integer Programming Approach and Improved Heuristic Algorithms, 2008, Ad Hoc Networks, (6), 5, 696-717. http://dx.doi.org/10.1016/j.adhoc.2007.06.006. Copyright: Elsevier B.V., http://www.elsevier.com

Both integer programming models and heuristic algorithms have been proposed for finding minimum-energy broadcast and multicast trees in wireless ad hoc networks. Among heuristic algorithms, the broadcast/multicast incremental power (BIP/MIP) algorithm is most known. The theoretical performance of BIP/MIP has been quantified in several studies. To assess the empirical performance of BIP/MIP and other heuristic algorithms, it is necessary to compute an optimal tree or a very good lower bound of the optimum. In this paper, we present an integer programming approach as well as improved heuristic algorithms. Our integer programming approach comprises a novel integer model and a relaxation scheme. Unlike previously proposed models, the continuous relaxation of our model leads to a very sharp lower bound of the optimum. Our relaxation scheme allows for performance evaluation of heuristics without having to compute optimal trees. Our contributions to heuristic algorithms consist of the power-improving algorithm successive power adjustment (SPA), and improved time complexity of some previously suggested algorithms. We report extensive numerical experiments. Algorithm SPA finds better solutions in comparison to a host of other algorithms. Moreover, the integer programming approach shows that trees found by algorithm SPA are optimal or near-optimal., Original publication: Di Yuan, Joanna Bauer and Dag Haugland, Minimum-Energy Broadcast and Multicast in Wireless Networks: An Integer Programming Approach and Improved Heuristic Algorithms, 2008, Ad Hoc Networks, (6), 5, 696-717. http://dx.doi.org/10.1016/j.adhoc.2007.06.006. Copyright: Elsevier B.V., http://www.elsevier.com

Both integer programming models and heuristic algorithms have been proposed for finding minimum-energy broadcast and multicast trees in wireless ad hoc networks. Among heuristic algorithms, the broadcast/multicast incremental power (BIP/MIP) algorithm is most known. The theoretical performance of BIP/MIP has been quantified in several studies. To assess the empirical performance of BIP/MIP and other heuristic algorithms, it is necessary to compute an optimal tree or a very good lower bound of the optimum. In this paper, we present an integer programming approach as well as improved heuristic algorithms. Our integer programming approach comprises a novel integer model and a relaxation scheme. Unlike previously proposed models, the continuous relaxation of our model leads to a very sharp lower bound of the optimum. Our relaxation scheme allows for performance evaluation of heuristics without having to compute optimal trees. Our contributions to heuristic algorithms consist of the power-improving algorithm successive power adjustment (SPA), and improved time complexity of some previously suggested algorithms. We report extensive numerical experiments. Algorithm SPA finds better solutions in comparison to a host of other algorithms. Moreover, the integer programming approach shows that trees found by algorithm SPA are optimal or near-optimal., Original publication: Di Yuan, Joanna Bauer and Dag Haugland, Minimum-Energy Broadcast and Multicast in Wireless Networks: An Integer Programming Approach and Improved Heuristic Algorithms, 2008, Ad Hoc Networks, (6), 5, 696-717. http://dx.doi.org/10.1016/j.adhoc.2007.06.006. Copyright: Elsevier B.V., http://www.elsevier.com

Both integer programming models and heuristic algorithms have been proposed for finding minimum-energy broadcast and multicast trees in wireless ad hoc networks. Among heuristic algorithms, the broadcast/multicast incremental power (BIP/MIP) algorithm is most known. The theoretical performance of BIP/MIP has been quantified in several studies. To assess the empirical performance of BIP/MIP and other heuristic algorithms, it is necessary to compute an optimal tree or a very good lower bound of the optimum. In this paper, we present an integer programming approach as well as improved heuristic algorithms. Our integer programming approach comprises a novel integer model and a relaxation scheme. Unlike previously proposed models, the continuous relaxation of our model leads to a very sharp lower bound of the optimum. Our relaxation scheme allows for performance evaluation of heuristics without having to compute optimal trees. Our contributions to heuristic algorithms consist of the power-improving algorithm successive power adjustment (SPA), and improved time complexity of some previously suggested algorithms. We report extensive numerical experiments. Algorithm SPA finds better solutions in comparison to a host of other algorithms. Moreover, the integer programming approach shows that trees found by algorithm SPA are optimal or near-optimal., Original publication: Di Yuan, Joanna Bauer and Dag Haugland, Minimum-Energy Broadcast and Multicast in Wireless Networks: An Integer Programming Approach and Improved Heuristic Algorithms, 2008, Ad Hoc Networks, (6), 5, 696-717. http://dx.doi.org/10.1016/j.adhoc.2007.06.006. Copyright: Elsevier B.V., http://www.elsevier.com

Both integer programming models and heuristic algorithms have been proposed for finding minimum-energy broadcast and multicast trees in wireless ad hoc networks. Among heuristic algorithms, the broadcast/multicast incremental power (BIP/MIP) algorithm is most known. The theoretical performance of BIP/MIP has been quantified in several studies. To assess the empirical performance of BIP/MIP and other heuristic algorithms, it is necessary to compute an optimal tree or a very good lower bound of the optimum. In this paper, we present an integer programming approach as well as improved heuristic algorithms. Our integer programming approach comprises a novel integer model and a relaxation scheme. Unlike previously proposed models, the continuous relaxation of our model leads to a very sharp lower bound of the optimum. Our relaxation scheme allows for performance evaluation of heuristics without having to compute optimal trees. Our contributions to heuristic algorithms consist of the power-improving algorithm successive power adjustment (SPA), and improved time complexity of some previously suggested algorithms. We report extensive numerical experiments. Algorithm SPA finds better solutions in comparison to a host of other algorithms. Moreover, the integer programming approach shows that trees found by algorithm SPA are optimal or near-optimal., Original publication: Di Yuan, Joanna Bauer and Dag Haugland, Minimum-Energy Broadcast and Multicast in Wireless Networks: An Integer Programming Approach and Improved Heuristic Algorithms, 2008, Ad Hoc Networks, (6), 5, 696-717. http://dx.doi.org/10.1016/j.adhoc.2007.06.006. Copyright: Elsevier B.V., http://www.elsevier.com