Escalating cyber security threats and the increased use of Internet of Things(IoT)devices require utilisation of the latest technologies available to supply adequate protection.The aim of Intrusion Detection Systems(I...Escalating cyber security threats and the increased use of Internet of Things(IoT)devices require utilisation of the latest technologies available to supply adequate protection.The aim of Intrusion Detection Systems(IDS)is to prevent malicious attacks that corrupt operations and interrupt data flow,which might have significant impact on critical industries and infrastructure.This research examines existing IDS,based on Artificial Intelligence(AI)for IoT devices,methods,and techniques.The contribution of this study consists of identification of the most effective IDS systems in terms of accuracy,precision,recall and F1-score;this research also considers training time.Results demonstrate that Graph Neural Networks(GNN)have several benefits over other traditional AI frameworks through their ability to achieve in excess of 99%accuracy in a relatively short training time,while also capable of learning from network traffic the inherent characteristics of different cyber-attacks.These findings identify the GNN(a Deep Learning AI method)as the most efficient IDS system.The novelty of this research lies also in the linking between high yielding AI-based IDS algorithms and the AI-based learning approach for data privacy protection.This research recommends Federated Learning(FL)as the AI training model,which increases data privacy protection and reduces network data flow,resulting in a more secure and efficient IDS solution.展开更多
Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up t...Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.展开更多
Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a system...Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a systematic evaluation of typical studies. Results: The fundamental problem is that brain researchers fail to differentiate between biological mental disorders in which brain processes cause the disorder (notably schizophrenia, bipolar disorder, and melancholic depression) and learned mental disorders in which brain processes mediate but do not cause the disorder (which is the case with reactive depression, reactive anxiety, OCD, and PTSD). Researchers have been unsuccessful in identifying mechanisms in the brain that cause biological mental disorders, and will never be able to locate the innumerable specific neural connections that mediate learned mental disorders. Moreover, the author’s review of typical studies in this field shows that they have serious problems with theory, measurement, and data analysis, and that their findings cannot be trusted. Conclusions: Neuroscience-based brain research on mental disorders, unlike other neurological research, has been an expensive failure and it is not worth continuing.展开更多
Climate change and land use change pose a threat to the world’s biodiversity and have significant impacts on the geographic distribution and composition of many bird species,but little is known about how they affect ...Climate change and land use change pose a threat to the world’s biodiversity and have significant impacts on the geographic distribution and composition of many bird species,but little is known about how they affect threatened large-sized waterbird species that rely on agricultural landscapes.To address this gap,we investigated how climate and land use changes influence the distribution and nesting habitats of the globally vulnerable Lesser Adjutant(Leptoptilos javanicus) in Nepal.Between 2012 and 2023,we collected distribution data from 24 districts and nesting site information from 18 districts.In a nation-wide breeding survey conducted in 2020,we documented a total of 581 fledglings from 346 nests in 109 colonies.The ensemble model predicted a current potential distribution of 15%(21,637 km2) and a potential nesting habitat of 13%(19,651 km2) for the species in Nepal.The highest predicted current suitable distribution and nesting habitat was in Madhesh Province,while none was predicted in Karnali Province.The majority of this predicted distributional and nesting habitat falls on agricultural landscapes(>70%).Our model showed a likely range expansion of up to 15%(21,573 km2) for the distribution and up to 12%(17,482 km2) for the nesting habitat under SSP5-8.5 scenarios for the 2070s.The range expansion is expected to occur mainly within the current distribution and breeding range(Tarai and some regions of Siwalk),particularly in Lumbini and Sudurpashchim provinces,and extend to the northern portions(Siwalik and Mid-hill regions) in other provinces.However,the current Protected Areas and Important Bird and Biodiversity Areas are inadequate for providing optimal habitats for the species.Although the model suggests range expansion,the use of such novel habitats is primarily contingent on the availability and protection of large-sized trees(particularly Bombax ceiba,observed in 65% of colonies) in agricultural regions where nesting occurs.Therefore,our research suggests that agricultural landscapes should be prioritized in management plans for the conservation of the Lesser Adjutant in Nepal.展开更多
Objective: Psychedelic drug therapy is banned in all countries of the world except Australia, where the government regulatory watchdog, the Therapeutic Goods Administration, is planning to allow approved psychiatrists...Objective: Psychedelic drug therapy is banned in all countries of the world except Australia, where the government regulatory watchdog, the Therapeutic Goods Administration, is planning to allow approved psychiatrists, as of July 1, 2023, to prescribe psilocybin to treat depression and MDMA to treat post-traumatic stress disorder, a move precipitated by the U.S. Food and Drug Administration’s designation of these two drugs as “breakthrough therapy”. The objective of the present article is to demonstrate that the evidence on which the FDA and then the TGA relied is irretrievably flawed and should be dismissed. Method: Expert review of psychedelic therapy clinical trials and specifically of the methodology and measures used. Results: The present review demonstrates that the studies the U.S. FDA and the Australian TGA relied on to approve these two psychedelic drugs for therapy are irretrievably flawed. All future trials will follow the same procedure and are therefore bound to be flawed as well. Conclusions: Psychedelic drug studies have so far provided no trustworthy evidence of their effectiveness for treating mental disorders and are not likely to produce this evidence in the future. Psychedelic drug therapy is in any event impractical because of its specialized training requirements and very high treatment costs. It is also dangerous because false publicity about its effectiveness will almost certainly lead to unsupervised self-dosing with drugs that not only are illegal but have an unacceptably high addiction rate.展开更多
为了探讨环境激素类物质邻苯二甲酸二乙酯(DEP)和壬基酚(NP)对海洋微藻的联合毒性效应,选取杜氏盐藻(Dunaliellasalina)为受试生物,以环境激素对杜氏盐藻单一暴露的96 h EC50的毒性效应作为一个毒性单位(IU),采用毒性单位法比较研究了DE...为了探讨环境激素类物质邻苯二甲酸二乙酯(DEP)和壬基酚(NP)对海洋微藻的联合毒性效应,选取杜氏盐藻(Dunaliellasalina)为受试生物,以环境激素对杜氏盐藻单一暴露的96 h EC50的毒性效应作为一个毒性单位(IU),采用毒性单位法比较研究了DEP和NP单一暴露以及两者以三种不同混合比例(毒性单位比:1∶1、1∶4和4∶1)暴露对杜氏盐藻的细胞生长、叶绿体色素含量、可溶性蛋白含量、SOD活性以及最大光能转化效率(Fv/Fm)的影响。实验结果表明:DEP和NP单一暴露对杜氏盐藻的96hEC50分别为69.54 mg/L和1.47 mg/L,两种环境激素对杜氏盐藻均有抑制作用,且NP较DEP对杜氏盐藻的毒性更强。DEP和NP联合暴露较单一暴露对杜氏盐藻的细胞生长、叶绿体色素和可溶性蛋白的合成有较强的抑制作用,两种环境激素在毒性单位比为1:1、1:4、4:1三个比例水平上的联合毒性效应均表现为协同效应,其中比例为1:1的协同效应最强。展开更多
文摘Escalating cyber security threats and the increased use of Internet of Things(IoT)devices require utilisation of the latest technologies available to supply adequate protection.The aim of Intrusion Detection Systems(IDS)is to prevent malicious attacks that corrupt operations and interrupt data flow,which might have significant impact on critical industries and infrastructure.This research examines existing IDS,based on Artificial Intelligence(AI)for IoT devices,methods,and techniques.The contribution of this study consists of identification of the most effective IDS systems in terms of accuracy,precision,recall and F1-score;this research also considers training time.Results demonstrate that Graph Neural Networks(GNN)have several benefits over other traditional AI frameworks through their ability to achieve in excess of 99%accuracy in a relatively short training time,while also capable of learning from network traffic the inherent characteristics of different cyber-attacks.These findings identify the GNN(a Deep Learning AI method)as the most efficient IDS system.The novelty of this research lies also in the linking between high yielding AI-based IDS algorithms and the AI-based learning approach for data privacy protection.This research recommends Federated Learning(FL)as the AI training model,which increases data privacy protection and reduces network data flow,resulting in a more secure and efficient IDS solution.
基金Research Supporting Project Number(RSPD2023R 585),King Saud University,Riyadh,Saudi Arabia.
文摘Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.
文摘Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a systematic evaluation of typical studies. Results: The fundamental problem is that brain researchers fail to differentiate between biological mental disorders in which brain processes cause the disorder (notably schizophrenia, bipolar disorder, and melancholic depression) and learned mental disorders in which brain processes mediate but do not cause the disorder (which is the case with reactive depression, reactive anxiety, OCD, and PTSD). Researchers have been unsuccessful in identifying mechanisms in the brain that cause biological mental disorders, and will never be able to locate the innumerable specific neural connections that mediate learned mental disorders. Moreover, the author’s review of typical studies in this field shows that they have serious problems with theory, measurement, and data analysis, and that their findings cannot be trusted. Conclusions: Neuroscience-based brain research on mental disorders, unlike other neurological research, has been an expensive failure and it is not worth continuing.
基金This work has been supported by CAS-SEABRI(Y4ZK111B01)In-ternational Science,and Technology Commissioner of Yunnan Province(202203AK140027)+2 种基金Yunnan Province Science and Technology Depart-ment(202203AP140007)Rufford Small Grants Foundation(31372-2)Tribhuvan University National Priority Area Research Grant(TU-NPAR-2078/79-ERG-04)。
文摘Climate change and land use change pose a threat to the world’s biodiversity and have significant impacts on the geographic distribution and composition of many bird species,but little is known about how they affect threatened large-sized waterbird species that rely on agricultural landscapes.To address this gap,we investigated how climate and land use changes influence the distribution and nesting habitats of the globally vulnerable Lesser Adjutant(Leptoptilos javanicus) in Nepal.Between 2012 and 2023,we collected distribution data from 24 districts and nesting site information from 18 districts.In a nation-wide breeding survey conducted in 2020,we documented a total of 581 fledglings from 346 nests in 109 colonies.The ensemble model predicted a current potential distribution of 15%(21,637 km2) and a potential nesting habitat of 13%(19,651 km2) for the species in Nepal.The highest predicted current suitable distribution and nesting habitat was in Madhesh Province,while none was predicted in Karnali Province.The majority of this predicted distributional and nesting habitat falls on agricultural landscapes(>70%).Our model showed a likely range expansion of up to 15%(21,573 km2) for the distribution and up to 12%(17,482 km2) for the nesting habitat under SSP5-8.5 scenarios for the 2070s.The range expansion is expected to occur mainly within the current distribution and breeding range(Tarai and some regions of Siwalk),particularly in Lumbini and Sudurpashchim provinces,and extend to the northern portions(Siwalik and Mid-hill regions) in other provinces.However,the current Protected Areas and Important Bird and Biodiversity Areas are inadequate for providing optimal habitats for the species.Although the model suggests range expansion,the use of such novel habitats is primarily contingent on the availability and protection of large-sized trees(particularly Bombax ceiba,observed in 65% of colonies) in agricultural regions where nesting occurs.Therefore,our research suggests that agricultural landscapes should be prioritized in management plans for the conservation of the Lesser Adjutant in Nepal.
文摘Objective: Psychedelic drug therapy is banned in all countries of the world except Australia, where the government regulatory watchdog, the Therapeutic Goods Administration, is planning to allow approved psychiatrists, as of July 1, 2023, to prescribe psilocybin to treat depression and MDMA to treat post-traumatic stress disorder, a move precipitated by the U.S. Food and Drug Administration’s designation of these two drugs as “breakthrough therapy”. The objective of the present article is to demonstrate that the evidence on which the FDA and then the TGA relied is irretrievably flawed and should be dismissed. Method: Expert review of psychedelic therapy clinical trials and specifically of the methodology and measures used. Results: The present review demonstrates that the studies the U.S. FDA and the Australian TGA relied on to approve these two psychedelic drugs for therapy are irretrievably flawed. All future trials will follow the same procedure and are therefore bound to be flawed as well. Conclusions: Psychedelic drug studies have so far provided no trustworthy evidence of their effectiveness for treating mental disorders and are not likely to produce this evidence in the future. Psychedelic drug therapy is in any event impractical because of its specialized training requirements and very high treatment costs. It is also dangerous because false publicity about its effectiveness will almost certainly lead to unsupervised self-dosing with drugs that not only are illegal but have an unacceptably high addiction rate.
文摘为了探讨环境激素类物质邻苯二甲酸二乙酯(DEP)和壬基酚(NP)对海洋微藻的联合毒性效应,选取杜氏盐藻(Dunaliellasalina)为受试生物,以环境激素对杜氏盐藻单一暴露的96 h EC50的毒性效应作为一个毒性单位(IU),采用毒性单位法比较研究了DEP和NP单一暴露以及两者以三种不同混合比例(毒性单位比:1∶1、1∶4和4∶1)暴露对杜氏盐藻的细胞生长、叶绿体色素含量、可溶性蛋白含量、SOD活性以及最大光能转化效率(Fv/Fm)的影响。实验结果表明:DEP和NP单一暴露对杜氏盐藻的96hEC50分别为69.54 mg/L和1.47 mg/L,两种环境激素对杜氏盐藻均有抑制作用,且NP较DEP对杜氏盐藻的毒性更强。DEP和NP联合暴露较单一暴露对杜氏盐藻的细胞生长、叶绿体色素和可溶性蛋白的合成有较强的抑制作用,两种环境激素在毒性单位比为1:1、1:4、4:1三个比例水平上的联合毒性效应均表现为协同效应,其中比例为1:1的协同效应最强。
