bluuebunny/crossref_metadata_2025 huggingface dataset:
Resonance characteristics and energy losses of an ultra-high frequency ZnO nanowire resonator
Authors: Cai Xianfa , Xu Lizhong
Published: December 2022

An ultra-high frequency (UHF, 300 MHz∼3 GHz) nano mechanical resonator based on defect-free zinc oxide nanowire (ZnO NW) was fabricated through a top-down processing method. Using UHF detection technology based on a lock-in amplifier, through optimized measurement of high-performance equipment, it was detected at room temperature that the ZnO NW resonator could operate at a resonance frequency of nearly 650 MHz and a quality factor Q ≈ 1000∼2500, and its force sensitivity could reach 1 f N·Hz−1/2. The deformation, driving force and first-order resonance frequency of the resonator were calculated using the continuum model and compared with the experimental data. The resonance characteristics of ZnO NW resonators under piezoelectric excitation were analyzed and compared with that under electromagnetic excitation. The effects of various loss factors on the resonance characteristics were analyzed, with emphasis on the generation mechanism of piezoelectric loss, clamping loss and eddy current loss and their effects on quality factor and force sensitivity. The ZnO NWs used in this paper have piezoelectric effect, which is rare in other NWs, and are difficult to be fabricated in a bottom-up manner. And experiments show that for ZnO NWs resonators, piezoelectric excitation has obvious advantages in Q value compared with electromagnetic excitation. Unlike the bottom-up wet etch processing method, the resonant beam structure is well protected by the top-down processing method to reduce internal defects, and the top-down fabrication method is easier to integrate into the fabrication process of integrated circuits, which provides great potential for the applications of NW resonators, such as quantum electromechanical systems and high-frequency signal processing.
Learning in a closed-loop brain-machine interface with distributed optogenetic cortical feedback
Authors: Goueytes Dorian , Lassagne Henri , Shulz Daniel E , Ego-Stengel Valérie , Estebanez Luc
Published: December 2022

Objective. Distributed microstimulations at the cortical surface can efficiently deliver feedback to a subject during the manipulation of a prosthesis through a brain-machine interface (BMI). Such feedback can convey vast amounts of information to the prosthesis user and may be key to obtain an accurate control and embodiment of the prosthesis. However, so far little is known of the physiological constraints on the decoding of such patterns. Here, we aimed to test a rotary optogenetic feedback that was designed to encode efficiently the 360° movements of the robotic actuators used in prosthetics. We sought to assess its use by mice that controlled a prosthesis joint through a closed-loop BMI. Approach. We tested the ability of mice to optimize the trajectory of a virtual prosthesis joint in order to solve a rewarded reaching task. They could control the speed of the joint by modulating the activity of individual neurons in the primary motor cortex. During the task, the patterned optogenetic stimulation projected on the primary somatosensory cortex continuously delivered information to the mouse about the position of the joint. Main results. We showed that mice are able to exploit the continuous, rotating cortical feedback in the active behaving context of the task. Mice achieved better control than in the absence of feedback by detecting reward opportunities more often, and also by moving the joint faster towards the reward angular zone, and by maintaining it longer in the reward zone. Mice controlling acceleration rather than speed of the joint failed to improve motor control. Significance. These findings suggest that in the context of a closed-loop BMI, distributed cortical feedback with optimized shapes and topology can be exploited to control movement. Our study has direct applications on the closed-loop control of rotary joints that are frequently encountered in robotic prostheses.
Assessment of distributed new energy-bearing capacity of new power systems with multisource complementary characteristics
Authors: Li Jifeng , Liang Xianming , Wang Yanbo , He Xingtang , Pan Feng , Wu Jun
Published: December 2022

A reasonable assessment of the bearing capacity of distributed power-generation sources in power systems is a key guarantee for the construction of new power systems with new energy sources as the core. In view of the fact that the current distributed new energy-bearing capacity assessment method has not yet established a systematic assessment index system and has not taken into account multisource complementarity, a new distributed energy-bearing capacity assessment method for power systems that takes into account the characteristics of multisource complementarity was proposed. First, a distributed new energy-bearing capacity assessment framework was constructed and the influencing factors of distributed energy-bearing capacity were analysed. Second, a multidimensional distributed power bearing-capacity assessment index system and calculation method considering thermal stability, short-circuit current, voltage deviation, and harmonics was proposed and the assessment process of distributed energy-bearing capacity was proposed. Finally, the validity and applicability of the proposed method were verified through actual case simulation.
Application and Study of kiln temperature control system based on PLC
Authors: Zhao Jing , Wang Weijun
Published: December 2022

Kiln is a kind of main heat consuming equipment built with refractory materials to calcine materials and products. The temperature control of kiln directly affects the efficiency of the system, product quality and output. In order to produce the desired product output and quality, the kiln temperature must be controlled within a certain range to meet the process requirements. Due to the uncertainty and large lag of kiln temperature, the traditional control can not guarantee the constant temperature. Now taking the kiln temperature as the research object, the PID control based on PLC controller is adopted for the temperature. The results show that the PID kiln temperature control based on PLC has ideal effect and wide application prospect.
Insulation voltage experimental study of the galvanic couple in flow seawater
Authors: Ji Dou , Li Chen , Tong Yude
Published: December 2022

The problem of insulation voltage selection in potential-difference detection method of insulation performance of electrical insulating metal pair in flowing seawater is discussed. In flowing seawater, 921A-B10 pair was taken as the research object to design the insulation corrosion test of the pair material. The natural corrosion test, the galvanic corrosion test and the simulated electrical insulation test of the pair material were carried out respectively. The test shows that the larger the analog insulation resistance of the pair material in series is, the smaller the galvanic corrosion current is, and the larger the voltage at both ends of the insulation resistance is. Finally, the range of insulation setting voltage is obtained.
Research on the application of vertical axis wind turbine in subway tunnel
Authors: Yu Xin , Wang Zheng , Xiang Pei
Published: December 2022

When the subway train is running at high speed in the tunnel, the originally still air in the tunnel is pushed by the train, so that the air in the tunnel is immediately accelerated, and in the same direction as the train travels, which is called the piston effect in the tunnel, also known as Piston wind. The wind speed of the piston wind in the tunnel is 7~9m/s, and the air volume is considerable. The vertical axis wind turbine has the characteristics of small size, low starting wind speed and high wind energy utilization rate, so it can use piston wind to generate electricity to supply power to lighting equipment and advertising lights in the tunnel, so as to achieve the purpose of energy saving and emission reduction.
The silicon-based anode in lithium-ion battery
Authors: Liu Yuyang
Published: December 2022

Lithium-ion batteries are now widely used in our society. Developing advanced anode material to improve the property of Lithium-ion batteries has aroused more and more attention in recent years. The silicon-based material is one of the most popular materials for the anode owning to the unique advantages of theoretically high capacity, low operating point, rich material resources, and environmental friendliness. However, the decay of capacity fading during the cycling resulting from huge volume change and poor conductivity of this kind of anode material significantly limited the applications. Thus, novel strategies need to be developed urgent. For this scope, the silicon-based components with different materials and structures have been developed. Here we summarized a series of silicon-based components, involving in oxide composite materials, silicon/metal oxide composite materials, Si/Carbon nanotubes composite materials, and graphene composite material, from the aspects of the preparation process, microstructure, and performance of these silicon-based anode materials.
Performance of Lithium Ion Battery with Graphene Microstructure in Cathode
Authors: Ye Zhanqiang
Published: December 2022

Lithium-ion battery is a promising energy source with high output voltage, large energy density, low auto discharge, and no memory effect. Graphene, as a dimensional carbon material, has excellent electrical conductivity, strong mechanical properties, a large specific surface area, which has been widely applied in lithium-ion battery for modifying the cathode material of lithium secondary batteries, thus significantly promoting the flow performance, conductivity, and cycling stability of Li secondary batteries. In this review, we discussed the excellent properties of various cathode materials based on graphene with different microstructures including three dimensional network structure, Core/Shell structure, layered structure, porous structure, and sandwich structure, which could provide motivations for improving the performance of the lithium-ion battery.
Control strategy for grid-connected inverters based on STATCOM reactive power compensation Research
Authors: Li Shuang , Jia Wenchao , Wang Sizhong , Yu Zonglai
Published: December 2022

The problem of grid-connected inverter reactive power compensation becomes a decisive factor for grid-connected power quality. To ensure the system unit power factor operation, this paper designs a reactive power compensation control strategy for grid-connected inverters based on STATCOM. On the basis of detailed analysis of the working principle of STATCOM, the grid-connected inverter model is built with the help of MATLAB simulation environment. The experimental results show that the use of STATCOM for grid-connected inverter reactive power compensation ensures stable grid-side output voltage of the grid-connected inverter and can improve the power factor of the system at the same time, which has certain reference significance for upgrading the grid-connected inverter design.
Research on multi-sensor fusion-based AGV positioning and navigation technology in storage environment
Authors: Yuan Chuanqian , Wang Ye , Liu Jun
Published: December 2022

Aiming at the problems of low positioning accuracy and large trajectory deviation when AGVs work in dynamic storage environments, an AGV positioning and navigation method based on multi-sensor data fusion is studied. The method is based on traceless Kalman filter (UKF) and adaptive Monte Carlo localisation (AMCL) algorithms to fuse three kinds of sensor data, namely LiDAR, inertial guidance system and ultra-wideband positioning system, to finally output the accurate attitude of the AGV [1]. Remoting data communication between the AGV and the host computer through TCP protocol, and the host computer remotely controls the AGV to achieve autonomous positioning and navigation after the sensor data is fused. Experiments are carried out on a MATLAB simulation experiment platform, and the results show that the positioning and navigation system has high positioning accuracy and trajectory fitting, and has certain practicality in dynamic storage environment.
RLS-based BeiDou Satellite High Precision Positioning for Power Device
Authors: Peng Ziping , Guo Kun , Yu Sheng , Ma Tao , Zhang Diecong
Published: December 2022

The BeiDou-3 navigation satellite system (BDS-3) has been officially put into use, which will provide wider, more accurate, and smarter industrial applications. BDS-3 positioning has advantages of stability, economical reliability and most importantly, high positioning accuracy, which is widely used in power systems, covering power dispatching, energy management, data acquisition, and system monitoring. However, in the positioning process of BDS-3, positioning accuracy will be affected by spatial and temporal interference factors. This paper addresses the problem of poor positioning accuracy under the interference influence of BDS-3, and proposes a Recursive Least Squares (RLS)-based adaptive high-precision positioning scheme to effectively reduce the influence of interference factors.
Open Capacity Model of Medium Voltage Transmission Line in Distribution Network Based on Load Data
Authors: Zhang Wei , Meng Xiaoli , Li Rui , Chen Hai , Gu Yi , Zhang Yi , Zhang Jialei
Published: December 2022

Due to the influence of load fluctuation, the power supply stability of distribution network is insufficient. Therefore, the open capacity model of medium voltage lines in the distribution network is constructed by using load data. Based on the introduction of time parameter, the load pressure of the distribution network is calculated by using the peak load of distribution network. According to the relationship between the pressure value of sustainable load of the distribution network and the pressure value under the actual power load, the open capacity model of medium voltage lines is constructed. The test results show that when the design model is used to set the open capacity of medium voltage lines, the fluctuation of the expected outage time and frequency of the distribution network system is small, which indicates that the stable power supply can be realized
Technical research of the Intelligent substation’s secondary maintenance safety measure system
Authors: Dong Haitao , Xu Yingjie , Wang Tao , Lin Guihua , Wang Yuying , Gao Zhanjun
Published: December 2022

Major changes have taken place during the secondary equipment maintenance and isolation of the intelligent substation and conventional substation in that the physical connection of the conventional cable has become invisible and not to be touched. This change, no undoubtedly, has added the difficulty for the relay protection staff to operate. The secondary maintenance safety measure system of the intelligent substation described in this thesis can automatically complete the writing and implementation of the secondary safety measure sheet by adopting Groovy rules and self-learning fuzzy inference mechanism. The safety measure system expert data base has been continuously improved through manual correction and self-learning technology, which has greatly improved the work efficiency of the site operators, and reduced the impact of the wrong implementation of the secondary safety measures on the normal operation of the power system.
Application of IEC60870-5-101 in distribution automation terminal remote operation and maintenance
Authors: Li Kewen , Chen Qianyi , Ou Shifeng , Chen Shaonan , Zhang Wei
Published: December 2022

The characteristics, structure of extended remote operation and maintenance protocol based on IEC60870-5-101, the normal or abnormal communication process of remote maintenance are introduced, and the transmission of operation and maintenance data between distribution master stations and distribution terminal units is effectively standardized. This paper expounds some common problems and solutions of remote maintenance under current wireless public network communication mode.
Research on emergency repair strategy based on load grade and economy
Authors: Sun Xiaoguang , Geng Jianyu , Geng Bin , Liu Kai , Hou Xu , Wang Yuanzhi
Published: December 2022

Distribution network plays the role of distributing electric energy in the power system, whether it can run normally relates to people’s production and life. In recent years, frequent natural disasters have caused large-scale failures of distribution networks, resulting in the interruption of a large number of load power supply, which has a huge impact on people’s lives and post-disaster recovery work. Therefore, it is very important to formulate scientific and efficient emergency repair strategies. This paper will study the power supply recovery and multi-fault rush repair of distribution network respectively from the two aspects of load grade and the economy of power grid operation, establish mathematical model, and use particle swarm optimization algorithm to solve, so as to provide a more efficient emergency plan for power supply recovery after disaster.
Research of 3D trajectory Hovering Points Determination Method of UAV Patrol Inspection Transmission Tower
Authors: Xu Li , Guo Hao , Fu Yanyi , Wang Zhigang , Li Zhihui , Hua Zoude , Li Peng , Luo Changhong , Wang Peng , Wei Yi , Chen Bin , Liu Shushan
Published: December 2022

It is necessary to set UAV hovering points before programming the trajectory of a UAV patrol inspection transmission tower body and accessories such as fittings and insulators. The choice of the hover point will affect the work safety and inspection efficiency of the UAV. Therefore, a 500kV UHV AC double-drum tower and UAV three-dimensional simulation model are established and Electromagnetic field is emulated at first. Finally, UAV hovering points are determined by considering the simulation results and functional parameters of UAV. The research method is of great significance for the determination of 3D trajectory Hovering Point Determination Method of UAV Patrol Inspection Transmission Tower.
Research on transformer fault voiceprint recognition based on Mel time-frequency spectrum-convolutional neural network
Authors: Wang Sen , Zhao Bingnan , Du Jianmin
Published: December 2022

A series of faults will occur during the operation of the transformer, which will aggravate its vibration and noise signals to a certain extent. In order to realize the detection and recognition of transformer related faults during uninterrupted operation, a voiceprint recognition model based on Mel time spectrum convolution neural network is proposed in this paper. According to the sound signal collected by the transformer in actual operation, Mel time domain spectrum as a data set of deep learning model can be obtained through feature extraction preprocessing and Mel filter dimensionality reduction. On this basis, the Mel time domain spectrum convolution neural network deep learning model is constructed, and Adam is used as the optimizer to optimize the data set through the super parameter optimization combination with multi classification cross entropy as the loss function, so as to realize the voiceprint recognition under four different operating faults of the transformer. The simulation results show that the identification model proposed in this paper is feasible and effective in fault identification.
Optimization and application of parameter identification error algorithm for steam turbine governing system
Authors: Zhu Longfei , Si Paiyou , Liu Shuangbai , Mei Long , Xie Changya , Zhang Teng , Hu Yuou
Published: December 2022

The parameter identification of the steam turbine speed governing system needs to be realized by the fitting of the measured response curve of the steam turbine active power. The national standard puts forward strict requirements on the error of the identification result. At present, error calculation is often realized by manual punctuation, which is a complicated process and greatly influenced by human judgment. Hence it needs to be improved urgently. In this paper, polynomial fitting and improved sliding window method are used to optimize the error identification algorithm of the steam turbine active power response curve. The visualization of the program is realized based on the Python language. The algorithm improves the data processing efficiency and reduces the influence of human judgment. The calculation results meet the standard requirements.
Short-term photovoltaic power generation power prediction method based on SOA-BP neural network
Authors: Wang Zeliang , Liang Huang
Published: December 2022

The size of photovoltaic power generation has a certain uncertainty, which affects the quality of photovoltaic power generation, and affects the safety and stable operation of the power grid. By predicting the photovoltaic power generation, this problem can be better solved. A photovoltaic power generation power prediction method combining SOA (Seagull optimization algorithm) and BP neural network is proposed. The convergence speed of BP neural network prediction model is relatively slow, and it is easy to fall into local optimum. Optimizing its weights and thresholds through SOA can improve these situations. Through experiments, Through experimental comparison, it is found that the BP neural network method optimized by seagull algorithm has higher accuracy in predicting photovoltaic power generation.
Single-phase Grounding Fault Location Technology Based on Edge Calculation of Fault Components of the Positive-sequence Current
Authors: E Zhenwei , Liu Jiulong , Wu Yingming , Yu Zhengzhi , Zhao Chuanzong , Yu Chunyan , Yuan Chengye
Published: December 2022

In the one-phase-to-ground fault of the distribution network, due to the difference in the distribution of the positive sequence current constituents of each line, the information contained in the fault path and the non-fault path also has a certain difference. On this basis, the edge of the fault constituent in the positive sequence current is used to locate the one-phase grounding. The method first uses phase current subtraction to multiply the period difference before and after the fault, and then uses the inverse transformation before and after the fault to determine the positive and null sequence constituents of the fault. Symmetrical composition. By analysing the amplitudes of the positive sequence and null sequence currents of the three-phase fault constituents, and according to the corresponding relationship between the amplitudes and the adaptive threshold, the location of the fault section is realized. A specific fault point location criterion and steps are given in this paper, and it is verified by ATP simulation software.
Improving the quality of fur semi-finished products due to improving the retanning process
Authors: Garifullina A R , Latfullin I I , Antonova M V , Abdullina V H
Published: December 2022

The article deals with information about the main studies with the identification of the process of retanning using plasma treatment of skin tissues of rabbit skins and non-isocyanate urethanes containing products in order to improving the quality of semi-finished products. The results of research in the chemistry field of tanning compounds and their influence on the characteristic properties and physical and mechanical parameters are given.
Application of high-frequency plasma modification to obtain protective materials with improved sorption properties
Authors: Morozova I I , Tikhonova N V , Timoshina Y A , Voznesensky E F , Faskhutdinova A F
Published: December 2022

In sorption technologies, surface modification of coals is widely used in order to increase their sorption capacity. The most promising method for improving the properties of materials of various structures is high-frequency plasma treatment. It was revealed that after the treatment of sorbents with low-pressure high-frequency capacitive plasma, materials are obtained with properties different from the original sorbent, characterized by increased sorption properties. Processes that affect the kinetics of adsorption and increase the sorption activity of activated carbon have been studied by FTIR spectroscopy.
Optimizing microhardness testing of metallic glasses
Authors: Đulbegović Alem Ben , Bilić Krešimir , Fetić Amra Salčinović
Published: December 2022

There are common protocols and standards for measuring the microhardness of materials. However, measuring this property requires special attention when the materials are tens of microns thick. In this paper, we present the results of measuring the Vickers microhardness of three samples of metallic glasses of significantly different thicknesses. We varied the force and the loading time. In addition, we investigated the influence of mechanical surface treatment on microhardness results. By analyzing the results, we determined the optimal conditions for measuring the microhardness of samples of this geometry.
Joint theoretical and experimental study on elastic electron scattering from a methane molecule
Authors: Vukalovic J , Maljkovic J B , Tökési K , Predojevic B , Marinkovic B P
Published: December 2022

We report on a combined experimental and theoretical study of elastic differential cross section DCS (E, θ) from methane molecule in the intermediate energy range (50-300eV), with experimental results limited to an angle interval of 25 to 125 degrees. Theoretical results are acquired using two approximations: a simple sum of individual atomic cross sections and the other with molecular effect taken into the account. The experimental setup based on a crossed beam technique comprising of an electron gun, a single capillary gas needle, and a detection system with a channeltron was used to measure differential cross sections. The absolute scale for the cross sections is obtained by a relative-flow method using argon gas as a reference. The dependence of DCS on the energy of incident electrons has been considered in detail. The results are analysed and compared with available theoretical and experimental data.
Augmented reality in teaching about physics: first findings from a systematic review
Authors: Vidak A , Movre Šapić I , Mešić V
Published: December 2022

Augmented reality (AR) makes it possible to overlay digital content onto our view of real-world phenomena. This potentially facilitates learning of physics by visualizing connections between concrete physics phenomena and abstract physics formalism. Here we present a part of our systematic review of earlier research on the use of augmented reality (AR) in school and university teaching physics topics. Our systematic review includes 60 articles published between 2012 and 2020, indexed in the Scopus and Eric databases. We analyzed the technological properties of AR for different content areas of physics as well as various methodological aspects of earlier AR research in physics education (e.g., educational level of participants, sample size, and research design). It has been shown that AR becomes increasingly popular in the physics education research community.
Effects of technologically-rich physics homework: findings from an experimental study
Authors: Simić B , Halilović A , Mešić V
Published: December 2022

Students’ learning outcomes in physics are significantly affected by the quality of outside-of-classroom learning experiences. A rich source of these experiences may be the physics homework. In this study, the effects of technologically-rich physics homework were evaluated. To that end a pretest-posttest experimental design has been used. 67 first-year students from the First Bosniak Gymnasium were randomly assigned to one of the three homework approaches. In the control group students received conventional homework about work and energy. Within the simulation-based approach students were expected to interact with simulations to investigate work and energy phenomena, whereas in the video-based approach students learned by analyzing a video in which the teacher interacted with the same simulations as mentioned above. Based on analysis of covariance we could find that the between-group differences on the conceptual posttest were not statistically significant,F(2, 47)=0.59,p=0.56. At the same time, students who learned by interacting with simulations expressed significantly more positive attitudes towards homework, compared to students from the video-based group (mean difference=1.88, p=0.038), as well as compared to students from the conventional group (mean difference=2.02, p=0.03). Simulation-based physics homework may be a powerful tool for helping the students to reach important affective learning outcomes.
An integrative analytical framework and evaluation system of water environment security in the context of agricultural non-point source perspective
Authors: Chen Shouji , Wang Jiayang
Published: December 2022

Agricultural non-point source pollution (ANPSP) caused a contradiction between economic growth and water environmental security protection. In order to understand the trade-off between social-economic development and water environmental security in the context of agricultural non-point source pollution, a Driving force-Agricultural non-point source pollution-Pressure-State-Response (DAPSR) model framework was proposed, and 23 indicators were selected to construct the evaluation system of water environment security in this study. And we take Ya’an City, China as case study from 2017 to 2019, the characteristics of water pollution was analyzed, and the water environment security was evaluated by method of particle swarm projection pursuit. The results show that: (1) Agricultural non-point source pollutant discharge in Ya’an generally shows a decreasing trend. (2) The agricultural non-point source pollution subsystem and the response subsystem have a great impact on water environment security. (3) According to the values of water environment security, Yucheng, Hanyuan, Tianquan and Lushan are basically safe in level III, Mingshan is unsafe in level IV, Yingjing is safe in level II, Shimian and Baoxing are safe in level II. (4) The degree of agricultural non-point sources is highly correlated with the water environment security. This study shows that the DAPSR model is feasible and practical, and can provide a scientific basis for the decision-making of regional agricultural non-point source pollution prevention and water environmental security protection.
Machine learning models to predict nitrate concentration in a river basin
Authors: Dorado-Guerra Diana Yaritza , Corzo-Pérez Gerald , Paredes-Arquiola Javier , Pérez-Martín Miguel Ángel
Published: December 2022

Aquifer-stream interactions affect the water quality in Mediterranean areas; therefore, the coupling of surface water and groundwater models is generally used to solve water-planning and pollution problems in river basins. However, their use is limited because model inputs and outputs are not spatially and temporally linked, and the data update and fitting are laborious tasks. Machine learning models have shown great potential in water quality simulation, as they can identify the statistical relationship between input and output data without the explicit requirement of knowing the physical processes. This allows the ecological, hydrological, and environmental variables that influence water quality to be analysed with a holistic approach. In this research, feature selection (FS) methods and algorithms of artificial intelligence—random forest (RF) and eXtreme Gradient Boosting (XGBoost) trees—are used to simulate nitrate concentration and determine the main drivers related to nitrate pollution in Mediterranean streams. The developed models included 19 inputs and sampling of nitrate concentration in 159 surface water quality-gauging stations as explanatory variables. The models were trained on 70 percent data, with 30 percent used to validate the predictions. Results showed that the combination of FS method with local knowledge about the dataset is the best option to improve the model’s performance, while RF and XGBoost simulate the nitrate concentration with high performance (r = 0.93 and r = 0.92, respectively). The final ranking, based on the relative importance of the variables in the RF and XGBoost models, showed that, regarding nitrogen and phosphorus concentration, the location explained 87 percent of the nitrate variability. RF and XGBoost predicted nitrate concentration in surface water with high accuracy without using conditions or parameters of entry and enabled the observation of different relationships between drivers. Thus, it is possible to identify and delimit zones with a spatial risk of pollution and approaches to implementing solutions.
Exploring vulnerability to heat and cold across urban and rural populations in Switzerland
Authors: de Schrijver Evan , Royé Dominic , Gasparrini Antonio , Franco Oscar H , Vicedo-Cabrera Ana M
Published: December 2022

Heat- and cold-related mortality risks are highly variable across different geographies, suggesting a differential distribution of vulnerability factors between and within countries, which could partly be driven by urban-to-rural disparities. Identifying these drivers of risk is crucial to characterize local vulnerability and design tailored public health interventions to improve adaptation of populations to climate change. We aimed to assess how heat- and cold-mortality risks change across urban, peri-urban and rural areas in Switzerland and to identify and compare the factors associated with increased vulnerability within and between different area typologies. We estimated the heat- and cold-related mortality association using the case time-series design and distributed lag non-linear models over daily mean temperature and all-cause mortality series between 1990–2017 in each municipality in Switzerland. Then, through multivariate meta-regression, we derived pooled heat and cold-mortality associations by typology (i.e. urban/rural/peri-urban) and assessed potential vulnerability factors among a wealth of demographic, socioeconomic, topographic, climatic, land use and other environmental data. Urban clusters reported larger pooled heat-related mortality risk (at 99th percentile, vs. temperature of minimum mortality (MMT)) (relative risk = 1.17 (95%CI: 1.10; 1.24), vs peri-urban 1.03 (1.00; 1.06), and rural 1.03 (0.99; 1.08)), but similar cold-mortality risk (at 1st percentile, vs. MMT) (1.35 (1.28; 1.43), vs rural 1.28 (1.14; 1.44) and peri-urban 1.39 (1.27–1.53)) clusters. We found different sets of vulnerability factors explaining the differential risk patterns across typologies. In urban clusters, mainly environmental factors (i.e. PM2.5) drove differences in heat-mortality association, while for peri-urban/rural clusters socio-economic variables were also important. For cold, socio-economic variables drove changes in vulnerability across all typologies, while environmental factors and ageing were other important drivers of larger vulnerability in peri-urban/rural clusters, with heterogeneity in the direction of the association. Our findings suggest that urban populations in Switzerland may be more vulnerable to heat, compared to rural locations, and different sets of vulnerability factors may drive these associations in each typology. Thus, future public health adaptation strategies should consider local and more tailored interventions rather than a one-size fits all approach.
On the structure of Besse convex contact spheres
Authors: Mazzucchelli Marco , Radeschi Marco
Published: December 2022

We consider convex contact spheres

Y
Y

all of whose Reeb orbits are closed. Any such

Y
Y

admits a stratification by the periods of closed Reeb orbits. We show that

Y
Y

“resembles” a contact ellipsoid: any stratum of

Y
Y

is an integral homology sphere, and the sequence of Ekeland-Hofer spectral invariants of

Y
Y

coincides with the full sequence of action values, each one repeated according to its multiplicity.
Margulis multiverse: Infinitesimal rigidity, pressure form and convexity
Authors: Ghosh Sourav
Published: December 2022

In this article we construct the pressure forms on the moduli spaces of higher dimensional Margulis spacetimes without cusps and study their properties. We show that the Margulis spacetimes are infinitesimally determined by their marked Margulis invariant spectra. We use this fact to show that the restrictions of the pressure form give Riemannian metrics on the constant entropy sections of the quotient moduli space. We also show that constant entropy sections of the moduli space with fixed linear parts bound convex domains.
Post-critically finite maps on ℙⁿ for 𝕟≥2 are sparse
Authors: Ingram Patrick , Ramadas Rohini , Silverman Joseph
Published: December 2022

Let

f
:

P

n

→

P

n

f:{\mathbb P}^n\to {\mathbb P}^n

be a morphism of degree

d
≥
2

d\ge 2

. The map

f
f

is said to be post-critically finite (PCF) if there exist integers

k
≥
1

k\ge 1

and

ℓ
≥
0

\ell \ge 0

such that the critical locus

Crit
f

\operatorname {Crit}_f

satisfies

f

k
+
ℓ

(

Crit
f

)
⊆

f
ℓ

(

Crit
f

)

f^{k+\ell }(\operatorname {Crit}_f)\subseteq {f^\ell (\operatorname {Crit}_f)}

. The smallest such

ℓ
\ell

is called the tail-length. We prove that for

d
≥
3

d\ge 3

and

n
≥
2

n\ge 2

, the set of PCF maps

f
f

with tail-length at most 

2
2

is not Zariski dense in the the parameter space of all such maps. In particular, maps with periodic critical loci, i.e., with

ℓ
=
0

\ell =0

, are not Zariski dense.
Nanotechnology: A Very Short Introduction
Authors: Moriarty Philip
Published: December 2022

Nanotechnology: A Very Short Introduction discusses the key scientific themes and concepts underpinning nanotechnology, including interatomic and intermolecular forces. It covers single atom imaging, quantum confinement, self-assembly, molecular machinery, and nanomagnetism. It also shows the science underpinning nanotechnology. What is nanotechnology and how will it affect people? This VSI describes nanotechnology as a staple of science fiction that has a chequered history when it comes to public perception. It explores the question of whether swarms of sentient nanomachines will ultimately take over the world or whether nanotech will give nothing more than improved sun creams.
Interaction effect between fasting plasma glucose and lipid profiles on mortality of peritoneal dialysis patients
Authors: Xu Yiping , Zhong Zhong , Li Yi , Li Zhijian , Zhou Yi , Li Zhibin , Mao Haiping
Published: December 2022

Background

Peritoneal dialysis (PD) patients have a high risk of abnormal glucose and lipids metabolism.

Objective

We investigated the effects of baseline fasting plasma glucose (FPG) as well as its interaction with lipid profiles on all-cause and cardiovascular disease (CVD) cause-specific mortality in PD patients.

Methods

A total of 1995 PD patients were enrolled. Kaplan–Meier survival curves and Cox regression models were performed to assess the association of FPG levels with mortality in PD patients.

Results

During a median (25th–75th quartile) follow-up period of 48.1 (21.8–77.9) months, 567 (28.4%) patients died, including 282 (14.1%) CVD deaths. Kaplan–Meier survival curves showed that all-cause and CVD cause-specific mortality increased significantly with elevated baseline FPG levels (Log-rank tests: both P-values <.001). However, with adjustment for potential confounding factors, baseline FPG levels were not significantly associated with all-cause and CVD cause-specific mortality. Nevertheless, a significant interaction between baseline FPG and low-density lipoprotein cholesterol (LDL-C) on all-cause mortality was found (P for interaction test: .013), and subgroup analyses further showed that all-cause mortality was significantly increased for baseline FPG ≥7.0 mmol/L compared with the normal reference (FPG <5.6 mmol/L) (hazard ratio 1.89, 95% confidence interval 1.11–3.23, P-value = .020) for patients with LDL-C ≥3.37 mmol/L only, but not for those with lower LDL-C levels (<3.37 mmol/L).

Conclusion

The significant interaction effect between baseline FPG and LDL-C on all-cause mortality showed that, for PD patients with LDL-C ≥3.37 mmol/L, higher FPG levels (≥7.0 mmol/L) were significantly associated with an increased risk of all-cause mortality and need more intensive management of their FPG by clinicians in the future.
Ketone body levels in wintering great tits Parus major in sites differing in artificial food availability
Authors: Kaliński Adam , Glądalski Michał , Markowski Marcin , Skwarska Joanna , Wawrzyniak Jarosław , Bańbura Jerzy
Published: December 2022

Ketone body levels, among other biochemical blood indices, are important indicators of the physiological condition of birds. Plasma ketone as an indicator of fasting and lipid use is strongly linked to demanding phases in the avian life cycle, such as migration or wintering. The main goal of this study was to check whether ketone body levels differ between the habitats in which individuals stay in winter. To test the above prediction, we used a portable point-of-care device to measure ketone body levels in wintering great tits (Parus major). We assumed that wintering in distinct habitats that differ structurally, particularly with respect to food availability, would affect the metabolic performance of birds and their physiological condition. Individual great tits were trapped in mist nets and blood-sampled in three distinct locations within the city: an urban parkland, the deciduous forest and a city centre. As expected, we showed that the mean ketone level was significantly higher in the area where artificial feeding was irregular than in two areas of regular feeding, indicating the more intense fasting state there. We also checked if the level of ketone bodies differs with respect to the sex of an individual, but we found no such difference.
Disgusting odors trigger the oral immune system
Authors: Anja Juran Stephanie , Tognetti Arnaud , Lundström Johan N , Kumar Lalit , Stevenson Richard J , Lekander Mats , Olsson Mats J
Published: December 2022

Recent research has characterized the behavioral defense against disease. In particular the detection of sickness cues, the adaptive reactions (e.g. avoidance) to these cues and the mediating role of disgust have been the focus. A presumably important but less investigated part of a behavioral defense is the immune system response of the observer of sickness cues. Odors are intimately connected to disease and disgust, and research has shown how olfaction conveys sickness cues in both animals and humans. This study aims to test whether odorous sickness cues (i.e. disgusting odors) can trigger a preparatory immune response in humans. We show that subjective and objective disgust measures, as well as TNFα levels in saliva increased immediately after exposure to disgusting odors in a sample of 36 individuals. Altogether, these results suggest a collaboration between behavioral mechanisms of pathogen avoidance in olfaction, mediated by the emotion of disgust, and mechanisms of pathogen elimination facilitated by inflammatory mediators.

Disgusting stimuli are associated with an increased risk of infection. We here test whether disgusting odors, can trigger an immune response in the oral cavity. The results indicate an increase level of TNFα in the saliva. This supports that disease cues can trigger a preparatory response in the oral cavity.
Immigration and teacher bias towards students with an immigrant background
Authors: De Benedetto Marco Alberto , De Paola Maria
Published: December 2022

We analyse the role of changes in the geographic concentration of immigrants in shaping teachers’ assessment of students’ performance. By using data on Italian students attending the fifth grade, we adopt an IV estimation strategy and, by controlling for student performance in blindly scored tests of proficiency, find that an increasing presence of immigrants in the local population negatively affects the way teachers evaluate immigrant students, as opposed to their peers, in non-blindly graded tests. We also reveal that the effect is mainly driven by schools located in smaller communities and in areas with lower overall levels of educational attainment and that it is unlikely to be related to the conduct of immigrant students who live in the areas experiencing sizable increases in immigration flows. In addition, older teachers tend to be more biased.
Defining vulnerability subgroups among pregnant women using pre-pregnancy information: a latent class analysis
Authors: Molenaar J M , van der Meer L , Bertens L C M , de Vries E F , Waelput A J M , Knight M , Steegers E A P , Kiefte-de Jong J C , Struijs J N
Published: December 2022

Background

Early detection of vulnerability during or before pregnancy can contribute to optimizing the first 1000 days, a crucial period for children’s development and health. We aimed to identify classes of vulnerability among pregnant women in the Netherlands using pre-pregnancy data on a wide range of social risk and protective factors, and validate these classes against the risk of adverse outcomes.

Methods

We conducted a latent class analysis based on 42 variables derived from nationwide observational data sources and self-reported data. Variables included individual, socioeconomic, lifestyle, psychosocial and household characteristics, self-reported health, healthcare utilization, life-events and living conditions. We compared classes in relation to adverse outcomes using logistic regression analyses.

Results

In the study population of 4172 women, we identified five latent classes. The largest ‘healthy and socioeconomically stable’-class [n = 2040 (48.9%)] mostly shared protective factors, such as paid work and positively perceived health. The classes ‘high care utilization’ [n = 485 (11.6%)], ‘socioeconomic vulnerability’ [n = 395 (9.5%)] and ‘psychosocial vulnerability’ [n = 1005 (24.0%)] were characterized by risk factors limited to one specific domain and protective factors in others. Women classified into the ‘multidimensional vulnerability’-class [n = 250 (6.0%)] shared multiple risk factors in different domains (psychosocial, medical and socioeconomic risk factors). Multidimensional vulnerability was associated with adverse outcomes, such as premature birth and caesarean section.

Conclusions

Co-existence of multiple risk factors in various domains is associated with adverse outcomes for mother and child. Early detection of vulnerability and strategies to improve parental health and well-being might benefit from focussing on different domains and combining medical and social care and support.
Changes in cell surface properties of Pseudomonas fluorescens by adaptation to NaCl induced hypertonic stress
Authors: Abu Quba Abd Alaziz , Goebel Marc-Oliver , Karagulyan Mariam , Miltner Anja , Kästner Matthias , Bachmann Jörg , Schaumann Gabriele E , Diehl Doerte
Published: December 2022

Determination of the effect of water stress on the surface properties of bacteria is crucial to study bacterial induced soil water repellency. Changes in the environmental conditions may affect several properties of bacteria such as the cell hydrophobicity and morphology. Here, we study the influence of adaptation to hypertonic stress on cell wettability, shape, adhesion, and surface chemical composition of Pseudomonas fluorescens. From this we aim to discover possible relations between the changes in wettability of bacterial films studied by contact angle and single cells studied by atomic and chemical force microscopy (AFM, CFM), which is still lacking. We show that by stress the adhesion forces of the cell surfaces towards hydrophobic functionalized probes increase while they decrease towards hydrophilic functionalized tips. This is consistent with the contact angle results. Further, cell size shrunk and protein content increased upon stress. The results suggest two possible mechanisms: Cell shrinkage is accompanied by the release of outer membrane vesicles by which the protein to lipid ratio increases. The higher protein content increases the rigidity and the number of hydrophobic nano-domains per surface area.