bluuebunny/crossref_metadata_2025 huggingface dataset:
The study of the X17 anomaly with the PADME experiment
Authors: Gianotti Paola ,   PADME collaboration
Published: September 2023

In dark matter studies, the absence of experimental evidences other than the astrophysical observations, has triggered new approaches. Nowadays, many particle physics experiments at accelerators are trying to contribute by looking for signals of hidden particles postulated by different theoretical extensions of the Standard Model. This results in a vaste hunting for new particles with a wide range of properties with the intention to also give reason to other unexplained particle physics phenomena. Within this scenario is inserted the Positron Annihilation into Dark Matter Experiment (PADME) ongoing at the Laboratori Nazionali di Frascati of INFN that is looking for signals of hidden particles by studying the annihilations of a positron beam with the electrons of a fixed target. PADME had, up to now, two data taking periods devoted to the search of a dark photon signal, but its setup turned out to be also suited to explore the existence of a protophobic new boson of mass 17 MeV/c
2 postulated to explain an anomalous effect observed by a Hungarian group while studying nuclear excited states. In this paper it is reported an overview of the PADME experiment and of the modifications implemented to allow a dedicated data taking at 282 MeV beam energy, meant to produce the new particle at resonance.
Ion-source development at the off-line LERIB test-facility at iThemba LABS
Authors: Segal S T , Bark R A , Abraham J , Anderson H , Baard S , Crombie A , Ellis C , Duckitt W , Cornelius B , Kohler I , Shirinda O , Van Schalkwyk P
Published: September 2023

The Low Energy Radioactive Ion Beam (LERIB) facility [1] will be used to produce low-energy radioactive-ion beams (RIBs) with energies up to 60 keV. Radioactive reaction products will be created by a 66 MeV proton-beam impinging on a target made of carbide disks, such as SiC [2]. These reaction products will then be ionized in a target-ion-source (TIS) and extracted as beam. The TIS design allows three ion-sources: a surface ion-source [3], a forced electron-beam induced arc-discharge (FEBIAD) ion-source [4], and a resonance-ionization laser ion-source, or RILIS. The surface-ionization source was commissioned with stable beams in October 2021. The production of ions from Group-1 elements was accomplished with beams of 39K+, 41K+ and 23Na+ where currents were measured in the μA range. This source may be advantageous for producing stable pilot-beams for future radioactive-beam experiments. The FEBIAD is still in development at present.
INFN-LNS facility upgrade for the Nuclear Physics Renaissance
Authors: Gammino S. , Tumino A. , Greco V. , Celona L. , La Cognata M. , Di Pietro A. , Musumeci M. S. , Russo A.D.
Published: September 2023

A broad range of Nuclear Physics research activities have been carried out at INFN-LNS until the summer 2020, when the accelerators were stopped for the upgrade. The upgrade of LNS is a project mainly funded by a PON-FESR (National Program for Research and Innovation) strategic line for boosting the research infrastructures, having its own goals, time-schedule and deadlines. In addition to such an action promoted by the Italian Ministry of Research, further funds have been made available from INFN budget. The end of the phase supported by the PON for procurement and tenders is currently set for the end of 2023. A series of actions will therefore be implemented to improve scientific opportunities for users. In particular, the focus is on the commissioning of the Tandem and Superconducting Cyclotron with the new set-up, completed by the renewal of the experimental areas and the commissioning of the new fragment separator FRAISE, also financed under the PON. The high-intensity program, including the determination of the nuclear matrix elements (NME) for the double beta decay and the study of EOS for nuclear matter with large neutron content, will be made feasible by these improvements to accelerators, beamlines and detectors. Some highlights of the whole activity as well as of the Applied Physics perspectives and the Astroparticle Physics multi-messenger program, strictly connected to the Nuclear Physics program, are given.
Young Professionals Mentoring Programme in The Nuclear Industry
Authors: Bellingan Nancy , Steinmetz Hans-Jürgen
Published: September 2023

The nuclear industry has been facing issues linked directly to the mixed feelings of the public opinion and national governments towards the use of nuclear energy for electricity production among others.

Different institutions are aware of it and published reports on the challenges identified in this field, including the IAEA (International Atomic Energy Agency) and ESK (German Commission on Waste Management).

In this paper is presented an analysis of said challenges and a possible solution, the network NANCY (Nuclear Applications newcomers CommunitY), an initiative currently in phase of development at the focus field Nuclear Waste Management, in the university of applied sciences FH Aachen, Germany.
Prospective appraisal of a formative nuclear and radiation physics at Nairobi
Authors: Angeyo HK , Kaniu IM , Mustapha AO , Massop AD
Published: September 2023

We provide a prospective appraisal of the evolution of the graduate nuclear and radiation physics program at the University of Nairobi underscoring its unique growth in the framework of relevant knowledge networks and a nascent nuclear power program. Due to the distinctive characteristics of the nuclear fuel cycle, there arose in Kenya especially nuclear security educational requirements for a proliferation-free nuclear power program as well as the need for provision of a broad spectrum of technical capacities to plan, regulate, and safely handle a nuclear power infrastructure. We detail how the graduate program centres on our newly established research line in nuclear forensics. Learning from this experience we propose, as a result, moving into nuclear photonics enabled by accelerators so as to play more key roles in accelerating capacity building embracing both nuclear and laser physics.
An introduction to computational complexity and statistical learning theory applied to nuclear models
Authors: Idini Andrea
Published: September 2023

The fact that we can build models from data, and therefore refine our models with more data from experiments, is usually given for granted in scientific inquiry. However, how much information can we extract, and how precise can we expect our learned model to be, if we have only a finite amount of data at our disposal? Nuclear physics demands an high degree of precision from models that are inferred from the limited number of nuclei that can be possibly made in the laboratories.

In manuscript I will introduce some concepts of computational science, such as statistical theory of learning and Hamiltonian complexity, and use them to contextualise the results concerning the amount of data necessary to extrapolate a mass model to a given precision.
Systematics of mean resonance spacing and average radiative width from random forest regression
Authors: Bormans J P , Wyngaardt S M , Wiedeking M , Malatji K L
Published: September 2023

The interaction of a nucleus with photons plays a key role in understanding a competition in nuclear reactions. The photon strength function (PSF) gives the average response of a nucleus to an electromagnetic probe. In this study, an estimation is performed of the mean resonance spacing and average radiative width of 22 nuclei in the range A = 46 – 90. The calculations for this analysis are done in TALYS. In addition, a machine-learning driven approach for determining experimentally obtained model parameters from the neutron/proton and mass number is given. A reasonable agreement within the uncertainties is achieved between the model dependent calculations, using TALYS, and results from random forest regression.
Enhanced Security Contraband Detection through Integration of Attention Mechanism in R3Det
Authors: Ye Chao , Ding Jiangang , Wang Huaizhi , Yang Ming , Tian Aojia , Li Wei
Published: September 2023

Detecting dangerous goods in security images is a challenging task. To overcome the challenges of localization difficulty and directional feature loss of contraband in X-ray images, our proposed solution, R3Det, employs the Convolutional Block Attention Module (CBAM). By integrating ResNeSt into the original detector, our detector includes a soft attention mechanism to redistribute weights among feature channels. This enhances the network’s ability to extract important features and facilitates extraction of target objects features under complex backgrounds. Subsequently, we introduced the spatial and channel attention mechanism during the connection between the backbone and the Feature Pyramid Network (FPN), enabling the model to focus on significant features while ignoring complex background information, then the following Feature Refinement Module to achieve feature alignment in a pixel-by-pixel manner. Our approach successfully achieved rotating target detection in the background of complex X-ray images. Through end-to-end training, our proposed method achieves a 2.6% improvement over the original detector, with a mean Average Precision (mAP) of 86.7%. Notably, our approach showed remarkable results in detecting sensors, pressure, and firetrackers. Now, we have deployed our proposed method on actual security machines for hazardous material detection tasks.
A Framework for False Image Detection with Sample-Oriented Intelligent Adversarial
Authors: Jun Li , Jiajie Zhang , Yongqiang Feng , Yanzhao Liu
Published: September 2023

To develop algorithms capable of automatically detecting and evaluating the authenticity of images and videos, researchers have focused on false image detection algorithms. These algorithms aim to identify the authenticity of images by distinguishing between real images and forged ones generated using false generation algorithms. In this paper, the main focus is on implementing a single-frame authenticated image detector using the concept of migration learning. The detector utilizes Inception ResNet v2, a target classification network pre-trained on a self-built military scene dataset. To enhance the dataset, a series of graphical enhancement algorithms are employed, enabling the classification network to learn the crucial differences between real and forged images. Additionally, Focal Loss is introduced to balance the dataset for various GAN-based image generation algorithms. As a result, the final forged target image detector achieves an impressive classification accuracy of 0.8908 on a large-scale sample test set.
Flame Detection Based on Improved YOLOv7
Authors: Wu Lumeng , Wang Yingfan
Published: September 2023

A flame detection algorithm with improved YOLOv7 is proposed to address the problems that small targets in flame detection are easy to be missed and misdetected, and are easily disturbed by bright objects during detection. In the improved algorithm, the SE attention module is introduced to enhance the perception of the model on the channel; ConvNeXt is used to retain the features of small target flames for small targets among flame images; Employing K-means ++ clustering algorithm to gain the anchor points that match the flame size more to enhance the detection accuracy.The results testify that the improved algorithm we proposed in this paper is higher than the YOLOv7 in terms of average accuracy and precision.
Low illumination image enhancement based on attention mechanism and global illumination estimation
Authors: Shen Linshuai , Wei Weimin , Chen Tao
Published: September 2023

Aiming at the problems of insufficient or excessive local brightness enhancement, color distortion, and excessive noise in the existing low-light image enhancement algorithms, a low-light image enhancement method combining attention mechanism and global illumination estimation is proposed. First, the illumination distribution map of low illumination image is obtained through the illumination distribution estimation network coupled with the attention gate mechanism. Then, the weight of the light distribution map is learned in the feature attention module. Finally, the image details are fused by the detail reconstruction module to create improved image. According to the experimental results, this method may effectively improve image brightness, contrast, and color in subjective visual effects while also enhancing objective evaluation indicators like PSNR, SSIM, and MSE when compared to some conventional methods.
Single Image Rain Removal Algorithm Based on U-Net and Vision Transformer
Authors: Cui Hua , Yang Zhiqiang , Shi Yanzi
Published: September 2023

Rain will significantly lower image quality, which will undoubtedly have an impact on how well outdoor computer vision systems operate, such as autonomous driving. This paper proposes a two-branch deep neural network consisting of an attention guided U-Net and Vision Transformer, which could capture intra-field details and cross-patch relationships to obtain good global and local deraining effects. In order to ensure both branches pose positive effects on the target derain task, we specifically design a patch boot image module to achieve complemented feature fusion, which adaptively selects informative intra-field regions guided by the patch-wise importance map. Moreover, Wasserstein distance between the prediction and reference image is applied as the objective function to pursue better image quality measurement. In comparison to existing algorithms, the suggested method may more effectively remove rain and restore the background details, according to qualitative and quantitative results on the public datasets Rain200L and Rain200H. On the aforementioned datasets, the peaks of the structural similarity (SSIM) and signal-to-noise ratio (PSNR) were 32.55/0.9476 and 26.12/0.8826, respectively.
FCA-Net: A Fast Inference and Channel Attention Based Network for Hyperspectral Image Classification
Authors: Ji Bo , Bai Lin , Wang Haijuan , Shen Jiaming , Chen Guoqiang , Jin Ying
Published: September 2023

Hyperspectral imaging (HSI) is a competitive remote sensing technique used in various fields such as land cover mapping and environmental monitoring. Each hyperspectral imaging (HSI) scene is comprised of numerous narrow and contiguous spectral bands, rendering the extraction of information from HSI data cubes a challenging and computationally intricate endeavor. Convolutional neural networks (CNNs) have garnered widespread adoption for HSI classification due to their impressive performance. Nevertheless, the substantial number of internal parameters within CNNs engenders high computational and memory requirements, resulting in inefficient floating-point operations per second (FLOPS), particularly when faced with frequent memory access and an abundance of operators. To address this issue, this paper proposes a novel framework named Fast Inference and Channel Attention-based Network (FCA-Net). Specifically, the framework introduces a lightweight convolutional layer and a channel attention mechanism (CAM) to enhance the extraction of spatial and spectral information within the network. The proposed FCA-Net significantly reduces computational costs while maintaining reliable classification results and can perform fast processing on GPU or even CPU, making it a promising option for embedded systems. Furthermore, the optimized global computational cost, including reduced demand for compute power and memory, results in lower energy consumption, which has previously been proven advantageous for improving deep model performance.
Similar Graph Face Clustering Based on Graph Convolutional Neural Network
Authors: Fang Mingming , Li Shengen , Wang Jian
Published: September 2023

Face clustering is primarily a method for grouping a large number of face images and has important applications in the fields of label-free face image annotation and image management. Traditional machine learning clustering algorithms do not work well on face image data and are unable to learn effectively on complex face image features. Recent research has turned to the use of graph convolutional neural networks (GCNs) to learn contextual information from neighbourhood features between face images for inference, which can significantly improve performance. Unlike the conventional link prediction of face data points and confidence prediction between vertices by using GCNs, for this paper a similarity graph based face clustering algorithm is proposed. Construction of subgraphs by K-nearest neighbour algorithm, Learn the similarity between the k-nearest neighbor subgraphs of each face instance by constructing subgraphs with the k-nearest neighbor algorithm. Using a bottom-up clustering strategy to merge subgraphs to complete the clustering, this algorithm improves the clustering results on complex face features by 20% and 7% compared to traditional machine learning methods such as K-means and DBSCAN respectively, improving the clustering accuracy and reducing the computational complexity.
Research on image quality evaluation and its application in image fusions
Authors: Xin Hongqiang , Li Chao , Li Yunchao , Wei Zhuo , Wang Jian , Zhang Jie , Qiu Chun
Published: September 2023

In view of the digital image in the process of acquisition, storage, processing and transmission due to the camera equipment, compression degree and transmission bandwidth caused by various distortion problems, this paper summarizes the image quality evaluation methods. Firstly, two methods of image quality evaluation, namely subjective evaluation and objective evaluation, are introduced, and then the relationship between subjective evaluation and objective evaluation is analyzed. Finally, the image quality evaluation method is successfully applied to the image fusion processing test, which provides ideas for the subsequent research on image quality evaluation methods.
A time-frequency method for induction motor fault feature extraction using instantaneous power signals
Authors: Sun A L , Duan C D
Published: September 2023

To solve the issue that the characteristic frequencies of the broken rotor bar fault (BRBF) are always submerged by the fundamental component during the stator current spectrum analysis in light loads, this paper proposes an effective approach based on the instantaneous power signal and the local maximum synchrosqueezing transform (LMSST). By multiplying the current and voltage, the instantaneous power signal can provide more fault features and enhance fault component amplitudes. The LMSST method is used to obtain a time-frequency analysis with more concentrated energy, and more fault characteristics are extracted from the reconstructed signal, which helps to accurately identify the motor BRBF.
ERNIE-based Named Entity Recognition Method for Traffic Accident Cases
Authors: Cheng Zibin , Duan Zongtao , Bu Nana , Liu Yuexia , Cao Jianrong , Gao Zhengge , Zuo Pengfei
Published: September 2023

Traffic accident case named entity recognition, which helps mine key information in traffic accident texts, plays a vital role in downstream tasks such as the construction of knowledge graphs in road traffic and intelligent policing. In this paper, we construct a named entity recognition model based on the EDE (Entity Data Enhancement)-ERNIE-Bidirectional Gated Recurrent Unit Network (BiGRU)-Conditional Random Field (CRF) to address the current situation of low traffic accident case data and poor recognition of long-text entities. First, the amount of accident case data is enhanced using the entity random substitution method. Next, the text data of traffic accident cases are characterized as a dynamic word vector using the ERNIE pretraining model. Then, the BiGRU network learns the long-distance dependency relationship in the text to enhance the effect of the model on long-text entity recognition. Finally, the result sequence is constrained by the CRF layer to realize the named entity recognition model. The experimental part uses data related to real traffic accident cases in a domestic area. The data enhancement method increases the data volume three times compared to the original data volume. Experimental results show that the EDE-ERNIE-BiGRU-CRF model achieves better F1 values, recall and precision achieved better performance than the entity recognition methods of BERT-BiGRU-CRF, ERNIE-BiGRU-CRF, ERNIE-BiLSTM-CRF, ERNIE-CRF, ERNIE, BiGRU-CRF, ROBERTA-wwm-ext-BiGRU-CRF and verify its effectiveness for entity recognition in traffic accident cases.
Spatial-temporal Traffic Flow Prediction Model Based on the GAT and BiGRU
Authors: Gao Yunmeng , Zhao Liang , Du Jin , Wang Junnan
Published: September 2023

Real-time and accurate traffic flow prediction is crucial for improving the safety, stability, and efficiency of intelligent transportation system. Considering that traffic flow prediction methods rarely analyze from the perspective of the road network, in this paper, a spatial-temporal traffic flow prediction model based on the combination of graph attention network (GAT) and bidirectional gated recurrent unit (BiGRU) neural network is proposed. Firstly, GAT is used to analyze the complex topology of the road network, effectively obtaining the spatial features of the road network. Secondly, BiGRU is used to learn the dynamic changes of traffic flow data, effectively obtaining the temporal features. Thirdly, the obtained spatial-temporal features are output by the fully connected layer to complete the prediction of future traffic flow. Finally, the model is validated and evaluated on the California highway dataset. The experimental results show that the accuracy of GAT-BiGRU model is better than other benchmark models in predicting future traffic flows transformation, especially in long-term prediction.
Design and implementation of regional integrated environmental measurement for China space station
Authors: Yi Yusheng , Fan Gaojie , Bai Linhou , Wei Bangyou , Zheng Yi , Qi Xin , Ying Le , Zhang Shuqi
Published: September 2023

The monitoring of cabin air pressure, temperature, humidity, microgravity and other environmental parameters is very important for the long-term and reliable operation of large manned spacecraft. Based on the characteristics of 1553B bus, a design method of regional integrated environmental measurement for the space station was proposed, which realized the high precision and reliable measurement of environmental parameters such as pressure, temperature, humidity and microgravity of china space station. The measurement data can accurately reflect the environmental changes of astronauts’ in-orbit living, working and extravehicular activities, which verifies the effectiveness of the design. It provides the necessary new principle application verification for higher precision pressure measurement in lunar landing missions.
Digital twin design of pneumatic classifier and its key technology
Authors: Yu Y , Gao S C , Cao Y N , Liu J X , Jiao Z W
Published: September 2023

The design scheme for a digital twin of the pneumatic classifier is proposed, which is associated with the physical entity. The key technologies such as visualization design and data acquisition are analysed in order to realize the digital management of the pneumatic classifier and operating process and monitor flow field characteristics and particle motion based on data analysis according to the digital twin. It aims to realize real-time monitoring, simulation and prediction of the classification performance of the complex pneumatic classification systems, and provide practical guidance for the optimal design of pneumatic classifier.
Analysis and Calculation of Inductor Parameter for PWM rectifier
Authors: Tao Ma , Lei Hou , Zhipeng Ma , Long Fu , Yusen Zhang , Zhen Sun , Zhixiang Zhang
Published: September 2023

In the PWM rectifier, the rationality of the AC side filter inductance design directly affects the performance of the whole system. It not only limits the power output, but also affects the dynamic and static response of the current loop. It has an important influence on the four quadrant stable operation of the motor, the isolation of the grid electromotive force and the harmonic suppression of the current. According to the waveform characteristics of the sinusoidal current, the maximum change rate of the current occurs at the zero-crossing point. In this paper, the inductor is designed to meet the requirement of the change rate of the current near the zero-crossing point, so as to meet the tracking requirement of the current at any time in the whole cycle. In addition, for the design of the AC side inductance, this paper comprehensively designs from the perspective of meeting the requirements of power index and meeting the requirements of suppressing harmonic current.
Permanent Magnetization Transformation and Performance Analysis of Small Power Three Phase Asynchronous Motor
Authors: Zhen Jinshuai , Xu Yanliang , Zhou Peng , Li Huixin
Published: September 2023

Oilfield pumping units are the main production machinery in the oilfield, and the electricity consumed accounts for about 60% of the oilfield’s electricity consumption. The requirements of the pumping unit for the electric motor are high starting torque, high efficiency, and a wide economic operating range. If an induction motor is used, in order to meet the requirements of high starting torque of the pumping unit, it is necessary to configure a large capacity induction motor. However, during normal operation, the average load rate is low, mostly under light or no-load operation, the efficiency and power factor are low, resulting in a large amount of waste of electrical energy. In this paper, the permanent magnetization of the induction motor is proposed. The stator remain unchanged, only grooves (straight/inclined) are cut on the outer surface of the rotor to place permanent magnets. The original asynchronous motor is converted to a permanent magnet motor. It can be used in actual oilfield exploitation engineering.
The operator algebra of cyclic orbifolds
Authors: Estienne Benoit , Ikhlef Yacine , Rotaru Andrei
Published: September 2023

We identify the maximal chiral algebra of conformal cyclic orbifolds. In terms of this extended algebra, the orbifold is a rational and diagonal conformal field theory, provided the mother theory itself is also rational and diagonal. The operator content and operator product expansion of the cyclic orbifolds are revisited in terms of this algebra. The fusion rules and fusion numbers are computed via the Verlinde formula. This allows one to predict which conformal blocks appear in a given four-point function of twisted or untwisted operators, which is relevant for the computation of various entanglement measures in one-dimensional critical systems.
A Review Paper on Properties and Applications of Nanofluids
Authors: Mohammed Ahmed A. , Dawood H.I. , Onyeaka Helen N.
Published: September 2023

A nanofluid is a liquid that contains nanometer-sized particles. Nanofluids are obtained by dispersing nanometer-sized particles in conventional base fluids such as water, oil, ethylene glycol, etc. Nanoparticles of materials such as metallic oxides (Al2O3, CuO), nitride ceramics (AlN, SiN), carbide ceramics (SiC, TiC), metals (Cu, Ag, Au), semiconductors (TiO2, SiC), single, double or multi-walled carbon nanotubes, alloyed nanoparticles (Al70, Cu30), etc., were used to prepare the nanofluids. This paper presents a procedure for preparing Nanofluids, the properties of Nanofluids, and their applications in various fields, including energy, mechanics, and biomedicine. Then it defines the parameter that challenges the use of Nanofluids in different applications and finally suggests directions for future research on Nanofluids. The thermal conductivity of the Nanofluids is improved at a very low (< 0.1%) percentage of suspended particles. Nowadays, Nanofluids are used efficiently in non-traditional energy resources in absorbing solar energy to increase the temperature.
A Review-strengthening of reinforced concrete beams with textile-reinforced concrete
Authors: Abd-Al-Naser Marwa , Habra Ibrahim S I
Published: September 2023

Numerous problems that can occur during regular building use may necessitate the need for reinforced concrete RC members to be strengthened. An increase in live loads or structural damage is two examples. Various techniques can be used to increase load-carrying capability. Concrete reinforcement with textile-reinforced materials (TRC) is a more recent option. For almost all active forces, this strengthening procedure is appropriate. For bending, shear, torsion, or axial forces, strengthening is an option. Due to their many appealing qualities, characteristics as their high specific strength (i.e., strength to weight ratio), resistance to corrosion, the convenience of use, speedy installation, and little variation in cross-section, (TRC) have become more and more popular among structural engineers for strengthening and retrofitting projects The conclusions made from the experimental results of members made of reinforced concrete strengthened in shear suggest that textile-mortar composites greatly increase shear resistance, with the gain increasing with the number of layers. This review focuses on strengthening RC beams in flexure by textile-reinforced concrete. According to the authors, TRC jacketing is a very promising technique for increasing reinforced concrete components’ confinement, in addition to their shear and bending capability, which is necessary for seismic retrofitting and strengthening.
Enhancing punching shear capacity of flat slab: review of strengthening and repairing techniques
Authors: Abed Al-jabar Mustafa R , Kadhim Muhammad J
Published: September 2023

A significant number of concrete flat slabs need to be strengthened against brittle punching shear failure due to conversion of existing buildings, material deterioration, the growth of standards, and detailed defects. Furthermore, there are some traditional approaches to strengthen and repair reinforced concrete slabs which can be either cumbersome or expensive. The repairing of the slabs is very important and not optional because, they will be lost without repairing and reconstruction may not be appropriate due to lack of time or other exceptional circumstances. There were many techniques to strengthening and repair the flat slab depend on suitable way and material availability for strengthening like CFRP sheets, TRM jackets, steel stiffeners, steel bolts, column capital, increasing slab thickness and many other techniques. Typically, the strengthening enhanced punching shear capacity, and the increment may reach 90%. Repair specimens’ punching shear capacity, which may be more than that of the control specimen and the repairing techniques can be used for strengthening. From presented studies, it was found that using the same technique for strengthening and repairing gave better results in strengthening, so strengthening slabs before damages occur is important and enhances resistance better.
Strengthening of RC columns under eccentric loads using NSM steel and GFRP bars
Authors: Al-Thairy Haitham , Al-Shimarry Nibras Atiaa
Published: September 2023

The behavior of eccentrically loaded RC columns strengthened by NSM steel and glass fiber reinforced polymer (GFRP) rebars is investigated in this study. A total of six RC column specimens have been cast in this study with dimensions of (150×150×1200) mm (width × height × length). Two column specimens are unstrengthened and considered as controls, while the other specimens are strengthened by the NSM method using steel bars and hybrid steel and GFRP rebars. All column specimens have been tested under concentric and eccentric loads with an eccentricity of 75mm up to failure. Experimental results in terms of crack patterns, modes of failure, and load-displacement curves are all monitored, recorded, and assessed. The experimental results have shown an improvement in the ultimate load capacity for all strengthened column specimens. Further, results have demonstrated that, under concentric load, the almost similar enhancement in the strength of NSM-strengthened RC column specimens using steel bars only and hybrid steel and GFRP bars. However, at eccentric load, the ultimate load capacity of the strengthened RC column was increased by 62% and 79.45% compared to the control column using NSM steel and hybrid steel, and GFRP, respectively. Finally, this study found that at e/h = 0.5 using GFRP in the tension zone increased the ultimate load by about 11% when compared to steel.
Retrofitting of reinforced concrete columns with honeycombed cover
Authors: Al-Ziady Sura F.
Published: September 2023

In this research, a significant attention has been given to the experimental investigation of retrofitting and rehabilitation of honeycombed reinforced concrete (RC) columns. Ten RC columns specimens were tested and discussed in the experimental tests; five of them are for the square section with a dimension of cross section (200 X 200) mm, and five for the circular section with a cross section diameter of (200) mm. The total length for both sections is (1200) mm. The honeycombed zone in the base and middle of specimens was considered as a percentage of the total columns. The honeycombed columns were repaired with cement-based materials prior to the test. All columns were tested axially until failure. For each tested RC columns, the ultimate load, cracking load, mode of failure, and load versus lateral and axial displacement were recorded. Test results showed the strength and load capacity of the treated column exceed the one for the control column with different percentages based on the cross-section of RC column, and location and size of the honeycomb defect. The increase in ultimate load ranges from 3% to 16% for square section, while for circular section the range of increase starts from 3% to 17%. It is worth noting that this percentage of increase is higher as the size of the honeycomb increases and vice versa.
Utilization of PET fiber and nanomaterial in concrete: Review of flexural concrete behavior
Authors: Odaa Sief Aldeen , Al-Hadithi Abdulkader Ismail , Mansoor Yousif A.
Published: September 2023

Concrete may gain maximum flexural strength to a certain percentage with the inclusion of plastic fiber. Because of the weakening bonding concerning the fiber and cement paste, it loses strength under compression at the same rate it gains. The optimal addition ratio must be established to add Polyethylene Terephthalate (PET) fiber to concrete to improve its mechanical and structural qualities. To decide what will change in the microstructure of the concrete and the traction link between the PET fiber’s surface, it is highly advised to use any nanomaterials with PET fibers. Concrete fabric’s characteristics may be enhanced with nanomaterials, thus increasing concrete brittle and proving its activity in case of combination with various fibers as composite materials. The high surface area for fine material can modify concrete texture, one of the properties which leads to increased compressive strength. So, there is a need to create more experimental research and analytical survey. All studies from 2010-2022 It has referenced.
Mechanical evaluation of sustainable concrete production from porcelain waste
Authors: Jawad Zahraa N , Hassan Muhammad A
Published: September 2023

Concrete has witnessed a great development in recent years, representing the production of reliable types of concrete to withstand the applied loads, high durability, and ease of implementation, as the preparation of concrete has become from remnants (sustainable materials) due to its availability and cheapness in addition to ridding the environment of these materials. This research demonstrates the use of porcelain tailings as a fractional substitute for coarse aggregate, Studying effect adds partial replacement on mechanical properties such as flexural testing, tensile strength, and wet density and then compares them with the reference mixture. In this research, the percentage of replacement of coarse aggregate with porcelain waste from weight is 25%, 35%, 50%, and maintaining the ratio of water to cement at 40% it observes that produces concrete with high tensile and flexural strength at replacement percent 50%.
Negative Impact of Traffic Congestion on Air Pollution and Estimation Delay Mode for Signalized Intersections in Babil City Utilizing SIDRA8.0 Plus Software
Authors: Alkizwini Ali Salah , Ahmad Nahla Yassub
Published: September 2023

Traffic congestion is one of the most important factors contributing to air pollution. Vehicle emissions account for a significant portion of this pollution. Estimate the negative impact of traffic congestion by empirical model for predicting total delay time as a function of traffic conditions and geometric features and calculating the quantities of gases emitted during the traffic congestion at the signalled intersection is the goal of this paper. Two signalized intersections in Babil City with different characteristics are select. video recording is used to measure traffic volumes during peak and off-peak times. Afield survey is used to measure geometric design elements, signal timings, phasing, and selected emissions of HC, CO, and CO2 in (kg/hr) are based on delay. with 95% confidence, a linear regression model predicted the delay model. according to the statistical analysis, both geometry and traffic characteristics have a substantial influence on delay time. The constructed regression model for estimating delay has a high degree of correlation with actual values. The proportion of the total width of the exit route of an intersection of straight-forward departing traffic to the total width of groups of lanes departing on the same exit route at the same phase at the stop line it is observed that although the SIDRA 8.0 PLUS delay overestimates the delay at the high (v/c) range, there is no noticeable difference with the field delay and the study will offer suggestions to transportation and public health officials on how to try eco-routing and deco-signal timing to lower the risk of air pollutants.
Investigating Sustainability Indicators for Urban Road Network — A Methodical Review Literature
Authors: Nemaa Z K , Al-Jameel H A , Mohammed H A
Published: September 2023

Transportation that is both socially and environmentally responsible is an important factor in climate change. However, urban sustainable mobility schemes have no universally accepted success criteria. Sustainability evaluation lacks a common language. This document groups sustainable mobility strategies to establish critical transport performance measures. Sustainable transportation trumps targets, criteria, and indicators. The following are the top priorities for urban multimodal sustainable transportation, in descending order: There are 13 social, 11 economic, and 9 environmental criteria. Each of the three basic criteria used most often in the study specifically addresses the environment. Since the literature’s attribution of criteria to sustainability elements is complex, it’s recommended to analyze their interrelationships. As previously demonstrated, small and medium-sized cities have a high sustainability value of in terms of population and urban area, but large cities can improve their sustainability by controlling urban sprawl and managing urban transportation demand with adequate public transportation. It is proposed that in the future, the interrelationships between the criteria be evaluated, as their allocation to the aspects of sustainability is ambiguous in the available literature. This article can assist mobility executives in making decisions about urban transportation concepts and project management. Making transportation more environmentally friendly is crucial to reducing climate change’s negative impacts.
Employment of Some Aquatic Plants for Removal of Cadmium, Lead, and Copper from the River Water
Authors: Kareem S F , Janna H
Published: September 2023

The world’s most valuable resource is water in addition to being essential to life, freshwater is also used in many other processes, including those that involve agriculture, industry, and human consumption due to interference with its quality, it continues to be a limited resource. Fresh potable water supply, particularly in urban areas, has been severely impacted by population increase, urbanization, and consumption. Therefore, the aim of this study was to understand the behavior of some heavy metals in the river waters via aquatic life represented by some aqua plants to achieve this three tanks of river water made from glass were prepared and injected with three heavy metals each which they are (copper, lead, and cadmium). The first tank represents the control (without any plants) while the second tank contains lentil plants moreover, the third tank contains the ceratophllum. The removal of heavy metals from river waters is enhanced by the presence of these plants using lentil plants and Ceratophyllum plants, respectively, led to removals of roughly 77% and 73% of the copper (Cu) content compared to the regular operation (control tank). For lead (Pb) removal, the Ceratophyllum removed about 72.6%, and the presence of lentil plant removes 52% of the Pb and only around 20% of the substance has been removed in the control tank. With ceratophullum present, there was a higher removal percentage of cadmium (45.9%)compared to tanks without aqua plants or lentil plants, which had removal rates of 21% and 42.3%, respectively. In general, necessary action to minimize the impact of discharging polluted wastewater must be taken to save aquatic life and the environment.
Fabrication of cellulose-based polymer electrolyte membrane with green solvent DMSO via N-TIPS technique
Authors: Ratri C R , Arundati A H , Pradana F D , Nugraha A F , Astutiningsih S , Chalid M
Published: September 2023

Solid polymer electrolyte membrane for Li-ion battery was fabricated via N-TIPS technique. To substitute commercially available polyolefin-based separator with more sustainable source, cellulose-based membrane was employed as polymer matrix. Green solvent dimethylsulfoxide (DMSO) was used to replace conventional solvents. Impedance measurement using electrochemical impedance spectroscopy was performed to determine ionic conductivity of the solid polymer electrolyte membrane. Room temperature ionic conductivity of the membrane in CR2032 battery cell was 1.1×10−4 mS/cm, indicating good performance and feasibility for Li-ion battery application. This result is hundred times higher compared to cellulose-based membrane fabricated via similar route using conventional N-methyl pyrrolidone (NMP) solvent (1.38×10−6 S/cm). Further dielectric properties measurement using temperature variation in an enclosed chamber showed that the polymer electrolyte membrane obeys Arrhenius behaviour.
Water Quality Analysis Using QUAL2Kw Model During The Rainy Season and Dry Season in Upper Citarum Watershed, West Java, Indonesia
Authors: Nufutomo TK , Muntalif BS , Ariesyady HD , Sudradjat A
Published: September 2023

The Increasing population in the upstream Citarum watershed area can trigger increased water pollution caused by anthropogenic pollution such as from domestic waste, agriculture, landfills, and settlements. The equilibrium of ecosystems is disrupted when there is an increase in excess pollutants such as suspended materials and nutrients that will cause eutrophication. The purpose of this study was to analyze river water quality from temperature, pH, DO, BOD, Total phosphate (PO4), and Nitrate (NO3) parameters from upstream Citarum watershed waters using a water quality model, namely Qual2Kw. This model is based on the Streeter-Phelps theory, which includes the natural purification process of river water. The Qual2Kw model can be used for decision-making to limit river water pollution. The locations reviewed in the upstream Citarum watershed area were five sampling points (SP), namely at Cisanti Outlets (1), Wangisagara (2), Koyod (3), after the Cisirung WWTP (4), and Nanjung (5). Site selection is based on sources of pollutants from anthropogenic activities that can pollute river water. The QUAL2kw model is used to simulate water quality and is used as a basis for calculating the carrying capacity of pollutant loads against the desired target water quality. The simulation results of a valid water quality model with the observation results are BOD, TSS, and NO3. and parameters such as temperature, pH, DO, and PO4 are invalid because they have errors below 25%. These three parameters (BOD, TSS, and NO)3 have exceeded the Indonesian government’s water quality standard values both in the dry and rainy season. These three parameters indicate that the high pollution in the upper reaches of the Citarum River is caused by pollutant sources from settlements, agriculture, and animal husbandry.
Development of emission reduction measures of particulate matter emitted from coal fired power plants in Indonesia
Authors: Muthiawaty G , Dirgawati M , Permadi D A
Published: September 2023

Currently, Indonesia has committed to achieve Net Zero Emissions (NZE) efforts on their Nationally Determined Contribution (NDCs) and at the same time focusing on air pollution abatement. One of the dominant emissions sources of particulate matter as well as Greenhouse Gases (GHGs) is from coal fired power plants. It contributes 50% to the total energy consumption in power generation, therefore the major power plant in Indonesia. Therefore, efforts to reduce GHGs and particulate emissions are needed to achieve the NZE target as well as to improve air quality. The research objective is to determine the particulate pollution load based on the Business as Usual (BaU) scenario and also under the emission reduction scenario for the year of 2030. Particulate pollution load was calculated using the emissions inventory methodology described in the brown cloud atmosphere workbook (ABC-EIM). Particulate emission reduction scenarios were developed using the assumption of full installation of Electrostatic Precipitator (ESP) technology to control PM emission. In 2030, the emission reductions PM10, PM2.5, Black Carbon (BC), and Organic Carbon (OC) are 57,854 ton/year, 57,854 ton/year, 432 ton/year, and 1,723 ton/year.
Spatio-temporal analysis of tuberculosis in Sungai Tabuk District, South Kalimantan, 2020-2021
Authors: Lasari H H D , Medyna I , Fadillah N A , Rosadi D , Fakhriadi R
Published: September 2023

Respiratory TB is a chronic infectious disease that is still a global public health problem. One of the efforts in anticipating the threat of an explosion of tuberculosis cases is to prioritize surveillance through spatial analysis to detect clustering of cases. Geographic Information Systems (GIS) can be used to describe the spatial distribution and identify areas where tuberculosis clustering is likely to occur so that it can be a source of information for policymakers in the health sector in implementing tuberculosis control program activities. This study aims to identify spatiotemporal clusters of Respiratory TB cases in Sungai Tabuk district from 1 January 2020 to 31 December 2021. This study is a spatiotemporal retrospective study conducted in Sungai Tabuk District using data on Respiratory TB case reports obtained from the surveillance data of the Banjar District Health Office from 2020 to 2021. This study used the Poisson model with the help of the SaTScan v10.1 application and visualization of cluster patterns using the Quantum GIS 3.28 application. This study found that there are 2 clusters of Respiratory TB in Sungai Tabuk district. The cluster in 2020 during January-April showed significant results (RR = 6.78, P-value = 0.0001) with the cluster center located in Sungai Tabuk Keramat Village and a cluster radius of 7.2 km from the center point. Meanwhile, the cluster in 2021 was not significant (RR=5.03, P-value=0.141). Factors affecting TB clusters in Sungai Tabuk district are sociodemographic factors and environmental factors. Local governments can increase case-finding efforts and increase health promotion related to Respiratory TB disease, healthy homes, and clean and healthy living behaviors in areas and communities located in risky locations.