bluuebunny/crossref_metadata_2025 huggingface dataset:
Review—Measurements of Ionizing Radiations Using Micromechanical Sensors
Authors: Alanazi Nadyah , Almutairi Maram , Muthuramamoorthy Muthumareeswaran , Alodhayb Abdullah
Published: May 2022

In this review paper, we discuss several micromechanical sensors methods for utilizing technologies to detect gamma and beta radiation. The bending and resonance-frequency shifts of microcantilever sensors exhibit high sensitivity to ionizing radiation. Quartz oscillators, as well as microcantilevers coated with different materials, can aid in increasing the sensor sensitivity. Introducing MEMS technology to hydrogen-pressure sensors increased the ability of the sensors to detect low doses of radiation. Quartz tuning forks show excellent sensitivity to radiation and prove to be good candidates for radiation detection. It has been reported as will be discussed in this review that a limit of detection of as low as 10−14 Gy was reported using quartz crystal oscillators.
Tuning ON/OFF Ratios in Diarylethene-Based Single- and Bilayer Molecular Junctions
Authors: Hnid Imen , Liu Mingyang , Frath Denis , Bellynck Sebastien , Lafolet Frederic , Sun Xiaonan , Lacroix Jean-Christophe
Published: May 2022

Through electrochemical deposition, photoswitchable single and bilayer molecular junctions based on diarylethene (DAE) and bisthienylbenzene (BTB) layers were fabricated. The electrical characterization of closed and open forms of DAE were investigated by C-AFM for two different layer thicknesses fixed at 2–3 nm and 8–9 nm, i.e. below and above the direct tunneling limit. Both layers switch between high and low conductance modes (“ON” and “OFF” states) when irradiated by UV and visible light. ON/OFF ratios of 2–3 and 200–400 were obtained for 3 nm- and 9 nm-thick DAE MJs, respectively. Next, we prepared 9 nm-thick MJs using a bi-layer system. The first layer (5 nm) is based on BTB oligomers. The second layer (4 nm) is based on DAE oligomers. The impact of this first layer on the switchable properties of the system, and on the photoresponse of the 9 nm-thick DAE-based MJs has been studied. The DAE/BTB bilayer generates new electronic functions combining photoswitching and photorectification. The open form of DAE/BTB shows low conductance and asymmetric I(V) curves while the closed form shows symmetric I(V) curves and high conductance. More importantly, unprecedented ON/OFF current ratios of over 10 000 at 1 volt were reproducibly measured.
Graded lower body negative pressure induces intraventricular negative pressures and incremental diastolic suction: a pressure-volume study in a porcine model
Authors: Berboth Leonhard , Zirngast Birgit , Manninger Martin , Steendijk Paul , Tschöpe Carsten , Scherr Daniel , Hinghofer-Szalkay Helmut G. , Goswami Nandu , Petersen Lonnie G. , Mächler Heinrich , Alogna Alessio
Published: May 2022

This study examined the effects of incremental lower body negative pressure (LBNP) from −15 to −45 mmHg on hemodynamic regulation using invasive pressure-volume assessment in closed-chest pigs. Graded preload reduction via LBNP induces negative left ventricular (LV) pressures while increasing LV suction and thus allowing the ventricle to eject below the equilibrium volume at the end of systole. Accordingly, LBNP-induced central hypovolemia is associated with increased diastolic suction.
ACE2 gene combined with exercise training attenuates central AngII/AT1 axis function and oxidative stress in a prehypertensive rat model
Authors: Chen Xiu-Yun , Lin Cheng , Liu Guo-Ying , Pei Chun , Xu Gui-Qing , Gao Lie , Wang Shi-Zhong , Pan Yan-Xia
Published: May 2022

Angiotensin-converting enzyme 2 (ACE2) gene in combination with exercise training (ExT) delayed the progression of hypertension via normalizing the blunted baroreflex sensitivity (BRS) and inhibiting sympathetic nerve activity (SNA). Its underlying mechanism may be related to the inhibition of AngII/AT1 axis function and central oxidative stress in the paraventricular nucleus (PVN) of prehypertensive rats.
OpenCBD: A Network-Encrypted Unknown Traffic Identification Scheme Based on Open-Set Recognition
Authors: Hu Xinyi , Gu Chunxiang , Chen Yihang , Chen Xi , Wei Fushan
Published: May 2022

The encryption of network traffic promotes the development of encrypted traffic classification and identification research. However, many existing studies are only effective for closed-set experimental data, that is to say, only for traffic of known classes, while there are often lots of unknown classes traffic in the real environment of open sets, and many studies have difficulty identifying the traffic of unknown classes and can only misclassify them as known classes. How to identify unknown traffic and classify known traffic in an open-collection environment is one of the focuses of traffic analysis research. Considering these problems, this paper proposes a novel solution, which applies the open-set recognition method to the unknown traffic identification, and constructs a model based on deep learning and ensemble learning. The method constructs a model based on a convolutional neural network and a transformer encoder and then uses a three-stage training and testing process, combined with a novel loss function, to generalize to the open space to form OpenCBD. Experiments on public datasets show that the proposed method is significantly better than other open-set identification methods. It can not only distinguish known traffic from unknown traffic but also identify specific classes of known traffic.
The Leaf Extract of Mitrephora chulabhorniana Suppresses Migration and Invasion and Induces Human Cervical Cancer Cell Apoptosis through Caspase‐Dependent Pathway
Authors: Nimlamool Wutigri , Chansakaow Sunee , Potikanond Saranyapin , Wikan Nitwara , Hankittichai Phateep , Ruttanapattanakul Jirapak , Thaklaewphan Phatarawat
Published: May 2022

Cervical cancer is rated to be the leading cause of cancer‐related death in women worldwide. Since screening test and conventional treatments are less accessible for people in developing countries, an alternative use of medicinal plants exhibiting strong anticancer activities may be an affordable means to treat cervical cancer. Mitrephora chulabhorniana (MC) is the newly identified species; however, its biological functions including anticancer activities have been largely unexplored. Hence, in this study, we were interested in investigating anticancer effects of this plant on the human cervical cell line (HeLa). MC extract was profiled for phytochemicals by TLC. This plant was tested to contain alkaloids, flavonoids, and terpenes. HeLa cells were treated with MC extract to investigate the anticancer activities. Cytotoxicity and viability of cells treated with MC were determined by MTT assay and Trypan blue exclusion assay. Cell migration was tested by wound healing assay, and cell invasion was determined by Transwell assay. The level of caspase 7, caspase 9, and PARP was determined by western blot analysis. We found that the leaf extract of MC strongly reduced cancer cell survival rate. This finding was consistent with the discovery that the extract dramatically induced apoptosis of cervical cancer cells through the activation of caspase 7 and caspase 9 which consequently degraded PARP protein. Furthermore, MC extract at lower concentrations which were not cytotoxic to the cancer cells showed potent inhibitory activities against HeLa cervical cancer cell migration and invasion. Mitrephora chulabhorniana possesses its pharmacological properties in inhibiting cervical cancer cell migration/invasion and inducing apoptotic signaling. This accumulated information suggests that Mitrephora chulabhorniana may be a beneficial source of potential agents for cervical cancer treatment.
Ananas comosus Peels Extract as a New Natural Cosmetic Ingredient: Oil-in-Water (O/W) Topical Nano Cream Stability and Safety Evaluation
Authors: Yahya Nur Azzanizawaty , Abdul Wahab Roswanira , Attan Nursyafreena , Abdul Hamid Mariani , Mohamed Noor Norhayati , Kobun Rovina
Published: May 2022

Ananas comosus peels (AcP) are among the agro-industrial biomasses contributing to a significant volume of waste in Malaysia. Thus, the AcP extract (AcPE) may prove useful for other applications, such as an ingredient in a nanocream for controlled delivery for dermal application. Therefore, this study aimed to develop an oil-in-water (O/W) nanocream using ingredients derived from the AcPE and test its stability alongside safety evaluation. The extract is a rich source of polyphenolic compounds viz., catechin, quercetin, and gallic acid. The study discovered that the optimized AcPE nano cream was stable against coalescence during the accelerated test but was influenced by Ostwald ripening over 6 weeks of storage at 4°C. Safety assessments affirmed the AcPE nano cream to be free of microbial contamination and heavy metals. The findings conveyed that the A. comosus nano cream is a good cosmetic ingredient and may contribute to the cosmeceutical industry’s new and safe topical products.
Management of Major Seed-Borne Fungi of Cowpea (Vigna unguiculata (L.) Walp) with Four Selected Botanical Extracts
Authors: Gyasi Eric , Kotey Daniel A. , Adongo Barnabas A. , Adams Fuleratu K. , Owusu Edmund O. , Mohammed Abdul
Published: May 2022

Seed-borne fungal pathogens present significant constrain to the production and conservation of many seed crops including cowpea. Infection of mature seeds by such pathogens could result in mycotoxin contamination, loss of viability, and decay of seeds. This study aimed to identify seed-borne fungi on 200 accessions of cowpea under cold storage at CSIR-Plant Genetic Resources Research Institute (PGRRI), Ghana. Also, the antifungal effect of seeds of Piper nigrum, Xylopia aethiopica, Aframomum melegueta, and fresh leaves of Cymbopogon citratus aqueous extracts (100% w/v) on the major seed-borne fungi identified on the cowpea seeds was determined. Seven fungal species belonging to five genera were identified from the seeds of the cowpea accessions evaluated. However, the diversity and infection levels of the pathogenic fungi recorded on the seeds were lower than that of the saprophytic fungi indicating minimal capacity of the seeds to spread pathogenic fungi on the field. Aqueous extract of Aframomum melegueta inhibited the growth of Fusarium verticillioides by 98.40%, Colletotrichum sp. by 97.83%, Aspergillus niger by 94.70%, and Aspergillus flavus by 63.38%. The only other aqueous extract that inhibited the colony growth above 60% was that of Piper nigrum which inhibited colony growth of Fusarium verticillioides by 71.7% and Colletotrichum sp. by 63.47%. Due to the benign effect of Aframomum melegueta extract on the environment and non-target organisms, its use as a seed protectant is highly recommended. Further studies to establish the spectrum of activity and dose levels of Aframomum melegueta extract are recommended.
Labeling of Genetically Modified (GM) Foods in Peru: Current Dogma and Insights of the Regulatory and Legal Statutes
Authors: Delgado-Zegarra Jaime , Alvarez-Risco Aldo , Cárdenas Carmen , Donoso Massiel , Moscoso Stephanie , Rojas Román Brenda , Del-Aguila-Arcentales Shyla , Davies Neal M. , Yáñez Jaime A.
Published: May 2022

The COVID-19 pandemic has affected and afflicted human lives and been a transformative catalyst leading to closure of many companies, disrupting mental health, and reducing access to food and exacerbating food insecurity. This presents an opportunity to reflect on and examine genetically modified (GM) foods and their effective legislative regulation for the benefit of consumers. This review presents a detailed analysis of GM foods’ regulation in Peru and the analysis of certain specific cases that show the need for greater regulation of the industry.
The Application of Antimicrobial Photodynamic Therapy (aPDT) in the Treatment of Peri-Implantitis
Authors: Zhao Tianyuan , Song Jungyul , Ping Yuzhuo , Li Meihua
Published: May 2022

Background. This literature review evaluates the mechanisms and efficacy of different types of antimicrobial photodynamic therapy (aPDT) for treating peri-implantitis by reviewing existing experimental studies to provide guidance for the clinical application of antibacterial photodynamic therapy (aPDT) in oral implants. Materials and Methods. From February 2001 to February 2021, we have collected 152 randomized controlled trials of aPDT for peri-implantitis by searching the experimental studies and clinical trials published in PubMed, Embase, Web of Science, and Google Scholar databases via online search. After screening the retrieved literature, we finally selected 10 statistically significant literature for evaluation and review. Results. Compared with the traditional nonsurgical treatment of peri-implantitis, the aPDT was superior to the traditional mechanical irrigation treatment group in terms of periodontal indexes PD, BOP, PLI, and postoperative effect, and the difference was statistically significant (

P
<
0.05

). Furthermore, the combination of the aPDT and other treatments shows the synergistic antibacterial effect, signifying better clinical effect in many aspects (

P
<
0.05

). In these 10 papers, by comparing the probe depth (PD), bleeding on probing (BOP), synosteosis, and periodontal pathogenic bacteria detection, etc., obtained after treating peri-implantitis by application of the antimicrobial photodynamic therapy, and using the SPSS data analysis software for statistical data processing, we found that the antimicrobial photodynamic therapy combined with other periodontal treatments has a more prominent postoperative effect. Meanwhile, the antibacterial photodynamic therapy with targeted action of photosensitizer has strong specificity to some bacteria, while the synthetic photosensitize for antibacterial photodynamic therapy can show good inactivation effect on broad-spectrum periodontal anaerobes without side effect. Conclusion. The experimental studies and clinical data of antibacterial photodynamic therapy for treating peri-implantitis show a good postoperative treatment effect. In addition, it did not develop resistance due to the use of antibiotic drugs. Owing to multiple advantages from combining antibacterial photodynamic therapy and other treatments, it is applicable for clinical treatment.
Secure Wireless Networks Based on Fuzzy Logic for Smart HVAC Systems in Small-Scale Industries
Authors: Sanober Sumaya , Goyal Deepak Kumar , Keshari Sudhir , Arslan Farrukh , Dugbakie Betty Nokobi
Published: May 2022

The traditional heating, ventilation, and air conditioning (HVAC) system depends on wired mechanical thermostats and regulators deployed at various points in the industrial environment for temperature monitoring. Due to ineffective dynamic changes according to the environment, the traditional HVAC system consumes more electrical energy. Next-generation wireless network (NGWN) systems play a vital role in improving the overall efficiency of the system by continuous monitoring and analysis. A small-scale industry using HVAC systems needs an active smart energy saver technique for maintaining an economical budget. This work uses MATLAB software to simulate and analyze the utilization of fuzzy-based NGWN to reduce the energy consumption requirements of small-scale manufacturing. In the model, a fuzzy rule is designed and applied to a small-scale enterprise divided into five sectors, one of which is temperature sensitive, with the goal of lowering the energy bill. The model employs fuzzy rules to enhance the NGWN, which minimizes the energy usage cost by 30% as compared with the traditional existing HVAC systems.
Study on Fault Diagnosis Method and Application of Automobile Power Supply Based on Fault Tree-Bayesian Network
Authors: Zhang Chunhua , Fang Wen , Zhao Baopeng , Xie Zhen , Hu Changning , Wen Hongzhuan , Zhong Tao
Published: May 2022

Among various fault types of automotive power faults, power supply UB + faults have the most complex relationship between fault signs and fault points and are difficult to diagnose. So this paper proposes a Bayesian network fault diagnosis model of automobile power supply based on fault tree. Firstly, based on the in-depth analysis of the principle of automobile power supply fault, the UB + fault tree model is constructed. The fuzzy Bayesian network model of UB + fault is constructed through the mapping relationship between fault tree and Bayesian network. Then, the prior probability of UB + fault points are obtained according to the five-year fault dataset of FAW Volkswagen Reck system, and the relevant conditional probabilities are determined by fuzzy set theory due to the lack of data and the uncertainty in expert scoring. Finally, the relevant fault point probability values are determined according to the Bayesian network inference algorithm in the case of single or parallel UB + fault sign occurring, and the fault diagnosis sequence is guided, further improving fault diagnosis efficiency.
The Application of AI Technology in GPU Scheduling Algorithm Optimization
Authors: Yan Zhancai , Liu Yaqiu , Shao Hongrun
Published: May 2022

With the rapid development of integrated circuit technology, GPU computing capabilities continue to improve. Due to the continuous improvement and improvement of GPU programming capabilities, functions, and performance, GPUs have been widely used in the field of high-tech general-purpose computers. This article is aimed at studying the optimization of GPU scheduling algorithm based on AI technology. Through a combination of theoretical analysis and simulation experiments, the concepts of artificial intelligence technology and GPU scheduling are explained, and the impact of GPU architecture and GPGPU load on the energy efficiency of GPGPU is explained. On the basis of comprehensive analysis of GPU cluster characteristics, a new GA-TP scheduling algorithm based on genetic algorithm was designed, and based on the energy efficiency of the cluster, a simulation verification platform was built for the accuracy of simulation. Experimental results show that the acceleration rate of the GA-TP algorithm is significantly lower than that of the HEFT algorithm, the average acceleration rate is reduced by nearly 25%, and the scheduling efficiency of the GA-TP algorithm is higher.
Mitigating Bias and Error in Machine Learning to Protect Sports Data
Authors: Zhang Jie , Li Jia
Published: May 2022

One of the essential processes in modern sports is doping control. In recent years, specialized methods of artificial intelligence and large-scale data analysis have been used to make faster and simpler detection of violations of international regulations on the use of banned substances. The smart systems in question depend directly on the quality of the data used, as high-quality data will produce algorithmic approaches of correspondingly high quality and accuracy. It is evident that there are many sources of errors in data collections and intentional algorithmic interventions that may result from cyber-attacks, so end-users of artificial intelligence technologies should be able to know the exact origins of data and analytical methods of these data at an algorithmic level. Given that artificial intelligence systems based on incomplete or discriminatory data can lead to inaccurate results that violate the fundamental rights of athletes, this paper presents an advanced model for mitigating bias and error in machine learning to protect sports data, using convolutional neural network (ConvNet) with high-precise class activation maps (HiPrCAM). It is an innovative neural network interpretability technique, wherewith the addition of Bellman reinforcement learning (BRL) and Broyden–Fletcher–Goldfarb–Shanno (BFGS) optimization; it can produce high-precision maps that deliver high definition, clarity, and the input and output capture when the algorithm makes a prediction. The evaluation of the proposed system uses the Shapley value solution from the cooperative game theory to provide algorithmic performance propositions for each of the produced results, assigning partial responsibility to parts of the architecture based on the impact that the efforts have on the relative success measurement, which it has been preset.
Study on Mechanical Properties and Energy Consumption of Fissured Sandstone with Different Dip Angles under Impact Load
Authors: Ping Qi , Wang Shuo , Wu Yulin , Sun Shijia , Shen Kaifan , Wang Chen , Gao Qi , Fang Chenglong
Published: May 2022

To study the dynamic mechanical properties and energy consumption of fissured sandstone with different dip angles under impact load, impact compression tests were conducted on seven groups of and intact and fractured sandstone specimens with different dip angles using the split Hopkinson pressure bar (SHPB) device with 0.3 MPa air pressure. The influence of dip fissures on the crushing shape, dynamic compressive strength, dynamic elastic modulus, dynamic peak strain, dynamic average strain rate, dynamic stress-strain curve, and energy consumption of rock specimens was systematically analyzed. The results show that the 45° fissure angle is the best fragile angle according to the failure mode and dynamic compressive strength of the specimen and that difference in specimen failure modes specimens is attributed to the existence of fractures with different dip angles. The dynamic elastic modulus reaches the minimum when the fissure angle is 45° and the maximum when the fissure angle is 90°. The dynamic peak strain is the lowest and minimal influence of fissure angle on the average strain rate of the specimen is presented when the fissure angle is 45°. From the stress-strain curves, the two specimen ends are most vulnerable to the relative sliding and dislocation of the lateral fissure angle during impact compression when the fissure angle is 45°. With stable incident energy in the test, a prominent relationship exists between the reflected energy, transmission energy, and energy consumption and the fissure angles. In addition, the fissure angle exhibits a prominent influence on reflected energy and the energy consumption of the specimen when the fissure angle ranges from 45° to 60°.
Prediction of Urban Street Public Space Art Design Indicators Based on Deep Convolutional Neural Network
Authors: Yu Shanshan , Wang Hao
Published: May 2022

This paper analyzes and studies the structure and parameters of the VGGNet network model and selects the most commonly used and efficient VGG-16 as the prototype of the improved model. A multiscale sampling layer is added at the end of the VGG-16 convolution part so that the model can input images of any size for training and testing while reducing the number of neurons in the fully connected layer. This improves the training speed of the model under the premise of ensuring the accuracy. This paper uses multisource street spatial data combined with geographic information spatial analysis technology to measure and evaluate the spatial quality of streets in the main urban area. From the three dimensions of vitality, safety, and greenness of urban street space quality, a systematic structure for evaluation and analysis of street space quality is constructed. Street vitality includes eight index factors: entrance and exit density, street furniture density, street sketch density, street characteristic landscape density, POI density, POI diversity, commercial POI ratio, and street population density. There are five index factors: degree, roadside parking occupancy ratio, traffic signal system density, sidewalk width proportion, and street facility density. We use ArcGIS to build an index factor information database for statistical analysis and visualization. According to the natural discontinuous point classification method, the safety level of urban street public space is divided into five grades. The sample size of the first four grades has a small fluctuation range. The sample sizes are 153, 172, 153, and 158, respectively, accounting for 21%, 23%, 21%, and 21% of the total street samples, of which the first two grades occupy a total of 44%, so 44% of the streets in the main urban area have a low-quality level of street space. Level 5 has a sample of 102 streets, accounting for 14%, with an average street space quality value of 0.43.
Applying the Reproducing Kernel Method to Fractional Differential Equations with Periodic Conditions in Hilbert Space
Authors: Saky Hoda , Abbasbandy Saeid , Shivanian Elyas
Published: May 2022

In this article, the reproducing kernel method is presented for the fractional differential equations with periodic conditions in the Hilbert space. This method gives an approximate solution to the problem. The approximate and exact solutions are displayed in the form of series in the reproduction kernel space. In addition, we provide an error analysis for this technique. The presented method is tested by some examples to show its precision.
Applications of Iron Oxide Nanoparticles against Breast Cancer
Authors: Hosseinkazemi Hessam , Samani Saeed , O’Neill Andrew , Soezi Mahdieh , Moghoofei Mohsen , Azhdari Mohammad H. , Aavani Farzaneh , Nazbar Abolfazl , Keshel Saeed Heidari , Doroudian Mohammad
Published: May 2022

Breast cancer is the most common cancer diagnosed in women, with an estimated 12% of women in the United States affected during their lifetime. Researchers have demonstrated that early detection, diagnosis, and treatment are pivotal to increasing survival. The advent of nanotechnology has yielded several novel advances and available modern methods within the clinic to detect and treat breast cancer. Inorganic nanoparticles are broadly utilized for cancer diagnosis and therapeutic purposes. Interestingly, these nanoparticles can also be attached to tumor‐specific ligands and used to deliver chemotherapeutic or hormonal agents with high levels of tumor selectivity. Iron oxide nanoparticles are one of the most commonly used nanomaterials, which have attracted much attention to detect and treat breast cancers, owing to their superparamagnetic characteristics. Computerized tomography and magnetic resonance imaging (MRI) utilizing iron‐based magnetic nanoparticles are promising approaches for the radiological detection of breast cancer. Here, we discuss the roles and recent applications of iron oxide nanoparticles in diagnosing and treating breast cancer.
Deep Reinforcement Learning-Based Path Control and Optimization for Unmanned Ships
Authors: Wu Di , Lei Yin , He Maoen , Zhang Chunjiong , Ji Li
Published: May 2022

Unmanned ship navigates on the water in an autonomous or semiautonomous way, which can be widely used in maritime transportation, intelligence collection, maritime training and testing, reconnaissance, and evidence collection. In this paper, we use deep reinforcement learning to solve the optimization problem in the path planning and management of unmanned ships. Specifically, we take the waiting time (phase and duration) at the corner of the path as the optimization goal to minimize the total travel time of unmanned ships passing through the path. We propose a new reward function, which considers the environment and control delay of unmanned ships at the same time, which can reduce the coordination time between unmanned ships at the same time. In the simulation experiment, through the quantitative and qualitative results of deep reinforcement learning of unmanned ship navigation and path angle waiting, the effectiveness of our solution is verified.
The Construction Method of Computer Network Security Defense System Based on Multisource Big Data
Authors: Ma Jie , Li Shuanbao
Published: May 2022

This article proposes a computer network security defense system model based on multisource big data, which makes the security of computer networks more complete because of the shortage of current computer network security defense systems. The current network security situation is analyzed, and the problems faced in the field of network security are pointed out; then, multisource big data is introduced, and the characteristics of the multisource big data model are analyzed. This article proposes an information system network security model, which formally describes the relationship between network behavior among nodes, security threats, network attacks, and defense capability of security devices in an information system. After that, a network security defense system measurement scheme is constructed based on hierarchical analysis, and quantitative indicators of defense effectiveness are defined in two dimensions: risk severity of security threats and defense response actions of security devices, which enables quantitative evaluation of the security defense system, and then identifies omissions and defects of the network security defense system. A defense system measurement and optimization system is designed based on the proposed network security system measurement and optimization scheme. The application analysis of the project is combined with the actual scenarios. Through the evaluation and optimization of the security defense system in the natural methods, it is proved that the network security defense system evaluation and optimization scheme proposed in this article has reasonableness and effectiveness in the actual application.
Research on the Change in Public Art Landscape Pattern Based on Deep Learning
Authors: Zhao Lei , Tang Congcong
Published: May 2022

With the limited design level of urban external space and place environment, however, the city image design and public art design play an important role in urban development, which leads to the lack of rational understanding that vague urban style is the effective implementation. In this article, a deep learning model is proposed to study the changes in public art landscape pattern in urban space, and it is constantly found that the changes in urban spatial layout have an impact on urban development. Firstly, the landscape index was analyzed effectively, and the Markov model was used to predict land use change, which provided a theoretical basis for the analysis of urban landscape change. Then the GeoSOS-FLUS model based on deep learning is used to make up for the lack of diversity of land use types by using the suitability probability calculation module of ANN and the adaptive inertia and competition mechanism, and the competition between different land use types is introduced. The experimental results show that the GeoSOS-FLUS framework based on deep learning model has good prediction effect and application ability.
Natural Herbal Medicine as a Treatment Strategy for Myocardial Infarction through the Regulation of Angiogenesis
Authors: Zhang Mu-xin , Song Yu , Xu Wan-li , Zhang Ling-xiao , Li Chao , Li Yun-lun
Published: May 2022

Aim of Study. Myocardial infarction is the number one cause of death worldwide. Existing treatment methods such as drugs and surgery cannot completely restore the structure and function of the ischemic heart. In recent years, therapeutic angiogenesis has received gradually increasing attention due to its fundamental therapeutic advantages of improving microcirculation and restoring blood supply in ischemic areas. This article mainly reviewed the mechanism and effect of angiogenesis-promoting herbs. Methods. We conducted a literature search on the bioactive components of medicinal plants and their effects on angiogenesis after MI. We searched for articles in Web of Science, MEDLINE, PubMed, Scopus, Google Scholar, and China National Knowledge Infrastructure databases before April 2021. Results. In this article, we summarized the mechanisms by which copper ions, microRNA, Akt1, inflammation, oxidative stress, mitochondria, and pericytes are involved in angiogenesis after myocardial infarction. In addition, we reviewed the angiogenic effects of natural herbal medicines such as Salvia miltiorrhiza Bunge Bunge, Carthamus tinctorius L., Pueraria lobata, Astragalus, Panax ginseng C.A. Mey., Panax notoginseng (Burkill) F.H. Chen, Cinnamomum cassia (L.) J. Presl, Rehmannia glutinosa (Gaertn.) DC., Leonurus japonicus Houtt, Scutellaria baicalensis Georgi., and Geum macrophyllum Willd. Conclusions. Some herbs have the effect of promoting angiogenesis. In the future, natural proangiogenic drugs may become candidates for the treatment of cardiovascular diseases.
Resource Allocation Optimization Based on Energy Efficiency in Green Cloud Radio Access Network
Authors: Gao Jing , Guan Xin , Zhang Shuyue , Meng Xiao
Published: May 2022

Compared with traditional cellular networks, cloud wireless access network (C-RAN) can save more energy consumption because it centrally processes the signals in the baseband unit (BBU) pool served by the cloud platform. Aiming at the limited fronthaul capacity of the fronthaul link caused by massive data and the huge energy consumption caused by the explosive growth of mobile traffic, an energy-saving resource management scheme that is powered by a mixture of on-grid and green energy is proposed in this paper. Specifically, a new network energy efficiency (EE) model is constructed. The RRH with hybrid energy to supply power of the model in response to green communication and the model can also realize two functions: information decoding and wireless charging at the same time. The total power consumption including remote radio head (RRH), fronthaul link, BBU pool, and wireless charging equipment of user equipment is considered. Based on network energy efficiency model, in addition to considering the user’s quality of service (QoS), data rate requirements, transmission power of RRHs, and maximum battery capacity constraints, the constraints of fronthaul link capacity constraints also are considered in this paper. In order to solve the proposed optimization problem, a joint strategy of power allocation, resource block (RB) allocation, and power allocation ratio adjustment is proposed in this paper. However, the objective function of energy efficiency optimization problem is nonconvex and cannot be solved directly. Therefore, an equivalent convex feasibility problem is reconstructed, and the optimal solution is obtained by Lagrange dual decomposition method. Simulation results show that the proposed resource allocation scheme can provide higher energy efficiency for the network.
Co-pyrolysis of Hardwood Combined with Industrial Pressed Oil Cake and Agricultural Residues for Enhanced Bio-Oil Production
Authors: Madhu P. , Vidhya L. , Vinodha S. , Wilson Shiny , Sekar S. , Patil Pravin P. , Kaliappan S. , Prabhakar S.
Published: May 2022

Lignocellulosic biomass is the potential raw material for the production of biofuels through pyrolysis. It is an effective technique for converting biomass to biofuels. However, biofuel from agricultural residues and woody-based feedstocks shows poor fuel properties due to higher oxygen content. Co-pyrolysis is a promising process to produce high-quality bio-oil by two or more different materials. Forestry, industrial, and agricultural outcomes are the ideal co-feedstocks for improved bio-oil quality. In this study, individual and co-pyrolysis of hardwood, pressed mustard oil cake and corncob were conducted at a temperature of 500°C. Before conducting pyrolysis experiments, thermogravimetric analysis was conducted to evaluate thermal degradation behavior. Through individual pyrolysis, corncob yielded a maximum bio-oil of 43.9 wt%. On the other hand co-pyrolysis on binary blends of hardwood and corncob produced maximum bio-oil of 46.2 wt%. Compared to individual pyrolysis, the binary blend produced more bio-oil, suggesting a synergistic effect between hardwood and corncob. The decreased bio-oil yield of 40.1 wt% during co-pyrolysis of ternary blends suggests negative synergistic effects prejudiced by the volatiles available in the biomass mixture. The improved quantitative synergistic results in the co-pyrolysis process give crucial information for the development of feed-flexible, higher bio-oil production and clean operating systems. The characterization studies on bio-oil by Fourier transform-infrared spectroscopy (FTIR), gas chromatography–mass spectrometry (GC-MS), and 1H NMR spectroscopy have shown that the bio-oil is a combination of aliphatic and oxygenated compounds. The analysis of the heating value shows that the bio-oil can be utilized as a fuel for heating applications.
Initial Phase I Safety Study of Gedatolisib plus Cofetuzumab Pelidotin for Patients with Metastatic Triple-Negative Breast Cancer
Authors: Radovich Milan , Solzak Jeffrey P. , Wang Chao J. , Hancock Bradley A. , Badve Sunil , Althouse Sandra K. , Bray Steven M. , Storniolo Anna Maria V. , Ballinger Tarah J. , Schneider Bryan P. , Miller Kathy D.
Published: May 2022

Purpose:

The PI3K pathway is dysregulated in the majority of triple-negative breast cancers (TNBC), yet single-agent inhibition of PI3K has been ineffective in TNBC. PI3K inhibition leads to an immediate compensatory upregulation of the Wnt pathway. Dual targeting of both pathways is highly synergistic against TNBC models in vitro and in vivo. We initiated a phase I clinical trial combining gedatolisib, a pan-class I isoform PI3K/mTOR inhibitor, and cofetuzumab pelidotin, an antibody–drug conjugate against the cell-surface PTK7 protein (Wnt pathway coreceptor) with an auristatin payload.

Patients and Methods:

Participants (pt) had metastatic TNBC or estrogen receptor (ER) low (ER and PgR < 5%, HER2-negative) breast cancer, and had received at least one prior chemotherapy for advanced disease. The primary objective was safety. Secondary endpoints included overall response rate (ORR), clinical benefit at 18 weeks (CB18), progression-free survival (PFS), and correlative analyses.

Results:

A total of 18 pts were enrolled in three dose cohorts: gedatolisib 110 mg weekly + cofetuzumab pelidotin 1.4 mg/kg every 3 weeks (n = 4), 180 mg + 1.4 mg/kg (n = 3), and 180 mg + 2.8 mg/kg (n = 11). Nausea, anorexia, fatigue, and mucositis were common but rarely reached ≥grade 3 severity. Myelosuppression was uncommon. ORR was 16.7% (3/18). An additional 3 pts had stable disease (of these 2 had stable disease for >18 weeks); CB18 was 27.8%. Median PFS was 2.0 months (95% confidence interval for PFS: 1.2–6.2). Pts with clinical benefit were enriched with genomic alterations in the PI3K and PTK7 pathways.

Conclusions:

The combination of gedatolisib + cofetuzumab pelidotin was well tolerated and demonstrated promising clinical activity. Further investigation of this drug combination in metastatic TNBC is warranted.
A Road Map for Designing Phase I Clinical Trials of Radiotherapy–Novel Agent Combinations
Authors: Brown Sarah R. , Hinsley Samantha , Hall Emma , Hurt Chris , Baird Richard D. , Forster Martin , Scarsbrook Andrew F. , Adams Richard A.
Published: May 2022

Radiotherapy has proven efficacy in a wide range of cancers. There is growing interest in evaluating radiotherapy–novel agent combinations and a drive to initiate this earlier in the clinical development of the novel agent, where the scientific rationale and preclinical evidence for a radiotherapy combination approach are high. Optimal design, delivery, and interpretation of studies are essential. In particular, the design of phase I studies to determine safety and dosing is critical to an efficient development strategy. There is significant interest in early-phase research among scientific and clinical communities over recent years, at a time when the scrutiny of the trial methodology has significantly increased. To enhance trial design, optimize safety, and promote efficient trial conduct, this position paper reviews the current phase I trial design landscape. Key design characteristics extracted from 37 methodology papers were used to define a road map and a design selection process for phase I radiotherapy–novel agent trials. Design selection is based on single- or dual-therapy dose escalation, dose-limiting toxicity categorization, maximum tolerated dose determination, subgroup evaluation, software availability, and design performance. Fifteen of the 37 designs were identified as being immediately accessible and relevant to radiotherapy–novel agent phase I trials. Applied examples of using the road map are presented. Developing these studies is intensive, highlighting the need for funding and statistical input early in the trial development to ensure appropriate design and implementation from the outset. The application of this road map will improve the design of phase I radiotherapy–novel agent combination trials, enabling a more efficient development pathway.
Prostate-Specific Membrane Antigen Expression and Response to DNA Damaging Agents in Prostate Cancer
Authors: Sheehan Beshara , Neeb Antje , Buroni Lorenzo , Paschalis Alec , Riisnaes Ruth , Gurel Bora , Gil Veronica , Miranda Susana , Crespo Mateus , Guo Christina , Jiménez Vacas Juan , Figueiredo Ines , Ferreira Ana , Welti Jon , Yuan Wei , Carreira Suzanne , Sharp Adam , de Bono Johann
Published: May 2022

Purpose:

Prostate-specific membrane antigen (PSMA) targeting therapies such as Lutetium-177 (177Lu)–PSMA-617 are affecting outcomes from metastatic castration-resistant prostate cancer (mCRPC). However, a significant subset of patients have prostate cancer cells lacking PSMA expression, raising concerns about treatment resistance attributable at least in part to heterogeneous PSMA expression. We have previously demonstrated an association between high PSMA expression and DNA damage repair defects in mCRPC biopsies and therefore hypothesized that DNA damage upregulates PSMA expression.

Experimental Design:

To test this relationship between PSMA and DNA damage we conducted a screen of 147 anticancer agents (NCI/NIH FDA-approved anticancer “Oncology Set”) and treated tumor cells with repeated ionizing irradiation.

Results:

The topoisomerase-2 inhibitors, daunorubicin and mitoxantrone, were identified from the screen to upregulate PSMA protein expression in castration-resistant LNCaP95 cells; this result was validated in vitro in LNCaP, LNCaP95, and 22Rv1 cell lines and in vivo using an mCRPC patient-derived xenograft model CP286 identified to have heterogeneous PSMA expression. As double-strand DNA break induction by topoisomerase-2 inhibitors upregulated PSMA, we next studied the impact of ionizing radiation on PSMA expression; this also upregulated PSMA protein expression in a dose-dependent fashion.

Conclusions:

The results presented herein are the first, to our knowledge, to demonstrate that PSMA is upregulated in response to double-strand DNA damage by anticancer treatment. These data support the study of rational combinations that maximize the antitumor activity of PSMA-targeted therapeutic strategies by upregulating PSMA.
Inhibition of the p53-MDM2 Interaction: Targeting a Protein-Protein Interface
Authors: Chène Patrick
Published: May 2022

MDM2 inhibits p53 transcriptional activity, favors its nuclear export, and stimulates its degradation. Inhibition of the p53-MDM2 interaction with synthetic molecules should therefore lead to both the nuclear accumulation and the activation of p53 followed by the death of the tumor cells from apoptosis. Inhibitors of the p53-MDM2 interaction might be attractive new anticancer agents that could be used to activate wild-type p53 in tumors. This review describes our current knowledge on the properties of the existing p53-MDM2 antagonists. Because the discovery of modulators of protein-protein interactions is an emerging field in drug discovery, the strategy used for designing inhibitors of the p53-MDM2 interaction could serve as an example for other protein interfaces.
Apolipoprotein L6, a Novel Proapoptotic Bcl-2 Homology 3–Only Protein, Induces Mitochondria-Mediated Apoptosis in Cancer Cells
Authors: Liu Zhihe , Lu Huimei , Jiang Zeyu , Pastuszyn Andrzej , Hu Chien-an A.
Published: May 2022

Cancer cells frequently possess defects in the genetic and biochemical pathways of apoptosis. Members of the Bcl-2 family play pivotal roles in regulating apoptosis and possess at least one of four Bcl-2 homology (BH) domains, designated BH1 to BH4. The BH3 domain is the only one conserved in proapoptotic BH3-only proteins and plays an important role in protein-protein interactions in apoptosis by regulating homodimerization and heterodimerization of the Bcl-2 family members. To date, 10 BH3-only proapoptotic proteins have been identified and characterized in the human genome. The completion of the Human Genome Project and the availability of various public databases and sequence analysis algorithms allowed us to use the bioinformatic database-mining approach to identify one novel BH3-only protein, apolipoprotein L6 (ApoL6). The full-length cDNA of ApoL6 was identified, cloned, and functionally expressed in p53-null colorectal cancer cells (DLD-1). We found that overexpression of wild-type ApoL6 induced mitochondria-mediated apoptosis in DLD-1 cells characterized by release of cytochrome c and Smac/DIABLO from mitochondria and activation of caspase-9, whereas ApoL6 BH3 domain deletion allele did not. In addition, overexpression of ApoL6 also induced activation of caspase-8. Furthermore, we showed that adenovirus harboring the full-length cDNA of ApoL6 induced marked apoptosis in a variety of cancer cell types, and ApoL6 recruited and interacted with lipid/fatty acid components during the induction of apoptosis. To our knowledge, this is the first example that intracellular overproduction of an apolipoprotein induces marked apoptosis.
Epidermal Growth Factor Modulates Tyrosine Phosphorylation of a Novel Tensin Family Member, Tensin3
Authors: Cui Yumin , Liao Yi-Chun , Lo Su Hao
Published: May 2022

Here, we report the identification of a new tensin family member, tensin3, and its role in epidermal growth factor (EGF) signaling pathway. Human tensin3 cDNA encodes a 1445 amino acid sequence that shares extensive homology with tensin1, tensin2, and COOH-terminal tensin-like protein. Tensin3 is expressed in various tissues and in different cell types such as endothelia, epithelia, and fibroblasts. The potential role of tensin3 in EGF-induced signaling pathway is explored. EGF induces tyrosine phosphorylation of tensin3 in MDA-MB-468 cells in a time- and dose-dependent manner, but it is independent of an intact actin cytoskeleton or phosphatidylinositol 3-kinase. Activation of EGF receptor is necessary but not sufficient for tyrosine phosphorylation of tensin3. It also requires Src family kinase activities. Furthermore, tensin3 forms a complex with focal adhesion kinase and p130Cas in MDA-MB-468 cells. Addition of EGF to the cells induces dephosphorylation of these two molecules, leads to disassociation of the tensin3-focal adhesion kinase-p130Cas complex, and enhances the interaction between tensin3 and EGF receptor. Our results demonstrate that tensin3 may function as a platform for the disassembly of EGF-related signaling complexes at focal adhesions.