bluuebunny/crossref_metadata_2025 huggingface dataset:
Low Temperature Cyclic Deposition/Etch (CDE) of Tensile-Strained Si:P
Authors: Hartmann Jean-Michel , Kanyandekwe Joël , Richy Jérôme , Veillerot Marc
Published: September 2022

Our aim was to assess the feasibility of the Low Temperature Cyclic Deposition / Etch (CDE) of tensile-Si:P for use in Raised Sources and Drains of n-type Field Effect Transistors. We were targeting high amounts of tensile strain and low resistivities in tensile Si:P layers grown at 550°C, with (i) mainstream Si2H6 + PH3 gases for the non-selective deposition of t-Si:P and (ii) HCl + GeH4 for the selective etches of poly-Si:P versus monocrystalline Si:P (to have selectivity on patterned wafers). Thanks to the use of 10 cycles CDE processes with various HCl + GeH4 etch durations on bulk and SiN-covered Si substrates, we showed that an etching selectivity of ~6 could be expected, for a-Si:P over t-Si:P, on patterned wafers. The presence of numerous nuclei on SiN-covered substrates nominally free of any bi-dimensional a-Si:P layers was evidenced by haze measurements, however, hinting at a lower effective selectivity. We then switched over to patterned SOI wafers with gates. We succeeded, when using 7 cycles CDE processes, in having almost full selectivity with 60s depositions and 40s etches / cycle, respectively. Maybe because there was a mix of a-Si:P and t-Si:P regions on such wafers, we had almost the same deposited t-Si:P thickness / CDE cycle (4.1–4.2 nm) whatever the HCl + GeH4 duration / cycle in the 15s–40s range. Meanwhile, there was a gradual disappearance of a-Si:P nuclei on dielectrics together with an “apparent” P concentration reduction from 4.0% down to 2.5% as that etch duration increased.
Avalanche Modeling in Mextram 505 and Implications on Circuit Simulations
Authors: Niu Guofu , Li Yiao , Zhang Huaiyuan , Scholten Andries , Willemsen Marnix
Published: September 2022

This paper presents recent advances in compact modeling of avalanche multiplication in Mextram 505, an industry-standard transistor model, including new model features, improved model implementations, and implications for SiGe HBT RF circuit simulation and device modeling.
Low Temperature Epitaxy of In Situ GaDoped Si1-XGex: Dopant Incorporation, Structural and Electrical Properties
Authors: Rengo Gianluca , Porret Clement , Hikavyy Andriy Yakovitch , Coenen Gitte , Ayyad Mustafa , Morris Richard J. H. , Pollastri Simone , De Souza Danilo Oliveira , Grandjean Didier , Loo Roger , Vantomme Andre
Published: September 2022

The effect of the growth temperature and the Ga precursor flow on the epitaxy of Si1-xGex:Ga is studied. These parameters are found to have a significant impact on the Ga surface segregation behavior. In particular, Ga in situ doping impacts the growth rate of the epilayer, the Si1-xGex alloy composition, and the onset of strain relaxation. The growth temperature can be used to modulate the Ga segregation, enabling the deposition of materials with enhanced dopant concentrations and improved electrical properties. The Ga local atomic environment was studied in both a Si0.4Ge0.6:Ga and a Ge:Ga sample by X-ray absorption fine structure. The local environment of the Ga determined confirmed that the majority of dopants occupy a substitutional position within the lattice.
3-Dimensional Self-Ordered Multilayered Ge Nanodots on SiGe
Authors: Wen Wei-Chen , Schubert Markus Andreas , Zöllner Marvin Hartwig , Tillack Bernd , Yamamoto Yuji
Published: September 2022

Three-dimensional (3D) self-ordered Ge nanodots in cyclic epitaxial growth of Ge/SiGe superlattice on Si0.4Ge0.6 virtual substrate (VS) were fabricated by reduced pressure chemical vapor deposition. By the Ge/SiGe superlattice deposition, dot-on-dot alignment and <100> alignment were obtained toward the vertical and lateral direction, respectively. Facets and growth mechanism of Ge nanodots and key factors of alignment were studied. Two types of Ge nanodots were observed, diamond-like nanodots composed of {105} and dome-like nanodots composed of {113} and {159} facets. The Ge nanodots tend to grow directly above the nanodots of the previous period as these regions show a relative higher tensile strain induced by the buried nanodots. Thus, this dot-on-dot alignment is sensitive to the SiGe spacer thickness, and it degrades when the SiGe spacer is over 82 nm. The Ge content of the SiGe spacer ranging 45-52% affects the lateral alignment and the size uniformity of Ge nanodots because of the strain balance between the superlattice and the VS. When the strain is balanced, 3D aligned Ge nanodots can be achieved.
(Invited) Improved Thin Film Transistor Model Predicts TFT Operation in the THz Range
Authors: Shur Michael , Liu Xueqing , Ytterdal Trond
Published: September 2022

Novel materials such as ZnO, InGaZnO, AMO-CNT, and organic materials and improved fabrication processes dramatically enhanced the achieved and projected thin film transistor (TFT) performance. The effective field-effect mobility of metal oxide TFT materials has reached values comparable to those for short-channel Si CMOS. We report on an improved compact model based on the RPI TFT model, the unified charge control model (UCCM), and the multi-segment TFT compact model. This improved model accounts for a non-exponential slope in the subthreshold regime by introducing a varying subthreshold slope and accounts for non-trivial capacitance dependence on the gate bias. The application of this new TFT model to the analysis of the TFT response showed that a TFT complementary inverter using the phase-matched THz signal feeding should yield a very sensitive detection of THz radiation impinging on a short channel TFT.
(Invited) Achieving Lower Power Logic Using P-Type Metal Oxide Thin Film Transistors
Authors: van Fraassen Niels C A , Han Sanggil , Niang Kham , Flewitt Andrew J. John
Published: September 2022

The excellent performance of n-channel thin film transistors (TFTs) based on amorphous oxide semiconductors has allowed integrated circuits based on NMOS logic to be successfully realized. However, future development will require CMOS logic to avoid excessive power dissipation and therefore p-channel TFTs are needed. Thin film p-type oxide semiconductors are rarely amorphous, and their microstructure has a significant impact upon both hole mobility and off-state current. In silicon MOSFETs, it is possible to scale device geometry to compensate for the lower hole mobility relative to electron mobility, but in TFTs this results in an excessive off-state current in the p-channel TFT as the off-state current also scales with geometry, which is not true to the same degree in silicon MOSFETs. Using new scaling rules that account for the off-state current, it is possible to optimize p-channel TFTs to operate alongside n-channel TFTs to achieve low power CMOS logic.
(Digital Presentation) Instability of α-Si:H TFTs under Simultaneous Ultraviolet Light Illumination and Different Bias Stresses
Authors: Liu Han-Wen , Hung Tzu-Cheng , Huang Bo-Xiang
Published: September 2022

The threshold voltage degradation and recovery phenomena of the α-Si:H TFTs stressed by DC or AC biases under with or without UV light illumination are investigated. For the negative DC bias stress, the threshold voltage shift of the stressed α-Si:H TFTs measured in the reverse sweep mode is smaller than that in the forward sweep mode, but the threshold voltage recovery is opposite, owing to the different increment of subthreshold swing of the α-Si:H TFTs after stressing. For the AC biases stresses, there are no significant difference of threshold voltage shift between the stressed α-Si:H TFTs measured by forward sweep and reverse sweep modes due to the less increment of subthreshold swing of the α-Si:H TFTs after stressing. There are more threshold voltage degradation but less recovery of the α-Si:H TFTs stressed by lower AC frequency with the higher negative bias in a cycle than those stressed by higher AC frequency.
(Invited, Digital Presentation) Ion Implantation for Amorphous-InGaZnO Sheet Resistance Control Technique
Authors: Ui Toshimasa , Yasuta Keisuke , Yamane Yuya , Tatemichi Junichi
Published: September 2022

As a next-generation electronics material, amorphous-InGaZnO (a-IGZO) film devices were investigated. In order to further utilize a-IGZO films, we carried out conventional ion of boron (B+) or neon (Ne+) implantations in a-IGZO thin films on glass and analyzed the implanted a-IGZO via Hall measurement with wet etching. In addition, a-IGZO thin film transistor processes with the implantation were carried out. As a result, we find that both ions drastically decrease a-IGZO sheet resistances. However, we observed oxygen vacancy area increase in the case of Ne+ implanted a-IGZO in 300 oC post annealing, which indicates Ne diffuses in a-IGZO film. On the other hand, B diffusion was not observed by depth profile comparison between the implanted samples with and without annealing. Furthermore, we extract key device parameters, such as effective channel length and ON/OFF current ratio, which can be applied to a-IGZO device processing.
(Digital Presentation) Effect of Active Layer Thickness on Organic Thin-Film Transistors
Authors: Moorthy Vijai M , Srivastava Viranjay Mohan
Published: September 2022

Thin-Film Transistors (TFTs) are a substantial technological advancement in recent decades for various applications. The source/drain electrode layer and organic active layer thicknesses of Organic Thin-Film Transistors (OTFTs) should be optimized for better device performance. In the current study, the authors have utilized the concept of OTFTs in the assessment of bipolar transport properties in active layer blends. It offers a strategy to improve the precision of the assessment. Thereafter, in this research work, impacts of active layer thickness on physical parameters of OTFT device performance have been realized. The study's findings show how these characteristics affect device performance and the need to optimize these variables in the device. The drain current of the high-performance P3HT: PCBM-based OTFT structure was approximately 4.3 µA for the thickness of 200 nm active layer, which has the highest performance.
(Invited) Oxide TFT Applications: Principles and Challenges
Authors: Kuo Yue
Published: September 2022

Oxide thin film transistors are emerging devices in high-speed, low- power active matrix displays. There are many other applications of this kind of device. The author analyzed these applications and categorized TFTs into three functions: as a control or readout unit for the attached device, as a switching device in circuits, and as a functional element itself in sensors. Examples on each function are shown and discussed. Future applications and challenges on oxide TFTs are presented.
(Invited) Deep Level Defects in AlN Studied By UV-Visible Spectroscopy
Authors: Dalmau Rafael , Kirby Samuel , Britt Jeffrey , Schlesser Raoul
Published: September 2022

Ultraviolet-visible (UV-Vis) spectroscopy was used to measure the optical absorption and emission from high-quality, 2-inch AlN substrates grown by physical vapor transport (PVT). Spatially uniform UV absorption coefficients below 20 cm-1 at 4.68 eV (265 nm) were demonstrated. The complementary spectroscopic data were used to elucidate the mechanism of UV absorption reduction in AlN containing high levels of the carbon impurity and co-doped with Si. Formation of a carbon-silicon defect complex, which shifted the absorption deeper in the UV, was demonstrated by photoluminescence (PL) emission and PL excitation (PLE) measurements. Additional deep levels in AlN related to cation vacancy complexes with oxygen were identified and discussed.
Molecular Dynamics Simulations of Cerium Ion Transport Phenomena in Polymer Electrolyte Membranes of Polymer Electrolyte Fuel Cells
Authors: Suzuki Hiroto , Mabuchi Takuya , Tokumasu Takashi
Published: September 2022

We analyzed the transport properties of cerium ions, which are added to improve the chemical durability of a polymer electrolyte membrane (PEM), using molecular dynamics simulations. For the analysis, the diffusion coefficient of cerium ions and the radial distribution function around sulfonic acid groups were obtained. The results show that at low water content, the diffusion coefficient is small because of the direct coordination of cerium ions to the sulfonic acid groups due to the small number of water molecules around the sulfonic acid groups. At high water content, water molecules gather around the sulfonic acid groups, and cerium ions are coordinated far from the sulfonic acid groups, resulting in a weaker binding than at low water content and an increase in the diffusion coefficient of cerium ions.
Chemical Stability Enhancement of Aromatic Proton Exchange Membranes Using a Damage Repair Mechanism
Authors: de Wild Tym , Nemeth Tamas , Nauser Thomas , Schmidt Thomas J. , Gubler Lorenz
Published: September 2022

Hydrocarbon-based fuel cell membranes are susceptible to radical-induced degradation. Such polymers commonly contain aromatic units, which react rapidly with HO·. Antioxidant strategies therefore need to focus on repairing intermediates formed upon radical attack to mitigate irreversible degradation. We summarize our recent ex situ g-irradiation studies on an aromatic model compound and in situ fuel cell tests of radiation grafted membranes with a polymer-bound crown ether-cerium complex to elucidate its antioxidant mechanism. Cerium is effective in reducing aromatic hydrocarbon membrane degradation and likely follows a catalytic mode of action.
(Digital Presentation) Effect of Iron Doping on Oxygen Reduction Activity of Zirconium Oxides Containing Carbon and Nitrogen Using Pyrazine Carboxylic Acid As Platinum Alternative Cathodes for PEFC
Authors: Watanabe Keita , Matsuzawa Koichi , Takeuchi Yuu , Ikegami Kaoru , Ohgi Yoshiro , Nagai Takaaki , Monden Ryuji , Ishihara Akimitsu
Published: September 2022

Fe-added zirconium oxide catalysts were synthesized by using pyrazine carboxylic acid to enhance oxygen reduction reaction (ORR) activity in acidic media. Fe-added zirconium oxide with a Fe/Zr atomic ratio of 0.1 showed highest ORR onset potential, 0.917 V vs. reversible hydrogen electrode among other zirconium oxide-based catalysts including the previous study. High quality active sites for ORR might be created by substitution of Zr4+ by Fe3+ in ZrO2 monoclinic structure. Although no use of carbon support caused a large particle size of zirconium oxides approximately 20~200 nm, the ORR activity drastically increased because of the creation of high quality active sites. We found that a positive correlation between a ratio of ZrO2 monoclinic structure and ORR activity. As a result, the use of pyrazine carboxylic acid was useful to create high quality active sites and a suitable electron conduction path.
Comparative Study of Platinum Nanoparticle Deposition on TiO2/BP and SnO2/BP Nanocomposites for the Oxygen Reduction Reaction
Authors: Müller-Hülstede Julia , Nagappan Nambi Krishnan , Bengen Nina , Uhlig Lisa Maria , Schonvogel Dana , Wagner Peter
Published: September 2022

For further commercialization of the proton exchange membrane fuel cell technology an improvement of the stability of commonly used Pt-based oxygen reduction reaction (ORR) catalysts is necessary. In this study SnO2- and TiO2-carbon nanocomposites using high surface area Black Pearls (BP) and commercial metal oxide nanoparticles were investigated as support materials for Pt. Homogenously distributed 40 wt.% Pt catalysts were obtained. When using TiO2-BP support an outstanding intrinsic activity but no stability improvement was observed, whereas the use of SnO2-BP as Pt support lead to a slightly lower ORR activity but an increased catalyst stability.
Temperature Distribution Analysis of PEM Electrolyzer in High Current Density Operation By Numerical Simulation
Authors: Yasutake Masahiro , Noda Zhiyun , Tachikawa Yuya , Lyth Stephen Matthew , Matsuda Junko , Nishihara Masamichi , Ito Kohei , Hayashi Akari , Sasaki Kazunari
Published: September 2022

An advantage of polymer electrolyte membrane water electrolysis (PEMWE) over other water electrolysis technologies is its ability to operate at high current densities. However, resistive heating during . In this study, the internal cell temperature distribution at high current densities up to 12 A cm-2 is evaluated through numerical simulation. The correlation between the temperature gradient in the cell and the flow rate of water supplied is examined. An increase in water supply is effective in minimizing high temperature gradients at higher current densities.
(Digital Presentation) Oxygen Evolution Reaction on Non-Precious Metal Oxide-Based Electrocatalysts With and Without Low Potential Scan in Acidic Solution
Authors: Matsuzawa Koichi , Kohara Yuma , Hirayama Soma , Yamada Satoshi , Ishihara Akimitsu
Published: September 2022

In order to develop non-platinum group metals anode electrocatalyst for the proton exchange membrane water electrolysis, the catalytic activity of Mn added Ta and Mo oxide-based electrocatalyst with and without low potential scan for the oxygen evolution reaction (OER) have been investigated. Both Mn added Ta and Mo oxide-based electrocatalyst without low potential scan (Mn-TaOx (E
low = 1.2 V) and Mn-MoOx (E
low = 1.2 V)) had much higher OER activity than that with low potential scan ((Mn-TaOx (E
low = 0.05 V) and Mn-MoOx (E
low = 0.05 V)) because the charge transfer resistance of both Mn-TaOx and Mn-MoOx (E
low = 1.2 V) were drastically smaller than that of Mn-TaOx and Mn-MoOx (E
low = 0.05 V). From SEM and XPS spectra, containing amount of Mn has maintained after electrochemical measurement in both bulk and surface of Mn-TaOx and Mn-MoOx without low potential scan (E
low = 1.2 V) while containing amount of Mn was reduced after electrochemical measurement in both bulk and surface of Mn-TaOx and Mn-MoOx with low potential scan (E
low = 0.05 V).
Design Optimization of Highly Efficient SOEC Co-Electrolysis Processes
Authors: Nakashima Yuhei , Tachikawa Yuya , Sasaki Kanzunari
Published: September 2022

High-temperature co-electrolysis of water and carbon dioxide using solid oxide electrolysis cells (SOECs) has attracted interest as an efficient synthesis gases production method. The SOECs and a fuel synthesis reactor are usually combined to produce hydrocarbon-rich fuel. In this study, we focused on investigating the effects of H2O/CO2 ratio of feed gas to the SOEC fuel electrode and gas and heat recycles on the fuel production efficiency were evaluated by mass and heat balance analysis. The results described that the amount of fuel production depended on the feed gas composition. In the case of increasing CO2 flow rate to the fuel electrode, the maximum amount of methane was produced and the efficiency of fuel production became 93.1% when the feed gas composition was controlled as H2O/CO2 = 4.32. These results indicate that the fuel production efficiency significantly depended on the operation condition of SOEC co-electrolysis and the system design.
Performance and Durability of Solid Oxide Electrolysis Cell Air Electrodes Prepared By Various Conditions
Authors: Ikegawa Kazutaka , Miyara Kengo , Tachikawa Yuya , Lyth Stephen Matthew , Matsuda Junko , Sasaki Kazunari
Published: September 2022

Fuel electrode materials are important for achieving higher performance and durability in solid oxide fuel cells (SOFCs), solid oxide electrolysis cells (SOECs), and reversible solid oxide cells (r-SOCs). On the other hand, the air electrode also faces performance and durability issues. For air electrodes, studies have been conducted on their performance and durability in SOFC operation, but the performance and durability of air electrodes in SOEC and r-SOC operation needs to be investigated in more detail. The electrochemical performance and durability of SOEC and r-SOC are evaluated by conducting electrolysis performance tests of LSCF-based air electrodes with different preparation conditions, electrolysis durability tests at the thermoneutral potential, and a 1000-cycle test in r-SOC mode.
(Digital Presentation) Influence of Preliminary Anodization of Amorphous Alloy Co75Si15Fe5Cr4.5Al0.5 in Ionic Liquid on Corrosion Resistance
Authors: Kuznetsova Irina , Lebedeva Olga , Kultin Dmitry , Kalmykov Konstantin , Philippova Svetlana , Leonov Alexander , Kustov Leonid
Published: September 2022

The article presents the results of studies on the formation of nanostructures on the surface of an amorphous alloy Co₇₅Si₁₅Fe₅Cr₄.₅Al₀.₅ using electrochemical anodizing at a controlled current in an ionic liquid BmimNTf₂. The corrosion (polarization resistance) stability of the alloy modified under different conditions of anodization in a Ringer's solution has been studied. The samples showed sufficient resistance to corrosion. Modification of the surface under certain anodizing conditions (5 mA, 200 s) leads to coating of the surface with oxide nanostructures – nanocells, which contribute to increasing resistance of the alloy to corrosion.
(Digital Presentation) Study of the Intervalence Charge Transfer in a 18NaCl+Na3SmF6 Model System By Quantum Chemical Methods
Authors: Stulov Yuriy V. , Kuznetsov Sergey A
Published: September 2022

The frontier orbital method showed a high informativity for the study of electron transfer in the model system 18NaCl+Na3SmF6. Structures having a high probability of electron transfer from the cathode to the samarium complex were observed when varying the transition state parameters. The influence of the full-symmetric oscillations Sm-F bonds and the boundary ion shift on the activation barrier, the frontier molecular orbitals energy and the delocalization character of the lowest unoccupied molecular orbital wave function in the samarium-containing model systems was systematically studied. This analysis allowed to identify the most probable structures of the transition state for the electron transfer process. The application of the method of frontier orbitals made it possible to determine the structure of the transition state of the complex SmF6
3- near the electrode surface with a small costs of machine time, using an agreement of the calculated and experimental values for the activation energy of electron transfer.
Review—Revisiting the Electroplating Process for Zn‐Metal Anodes: New Application of Traditional Electroplating Additive in ZIBs
Authors: Liu Zhenjie , Xi Murong
Published: September 2022

Because of its safety, cost-effectiveness, and environmental friendliness, aqueous zinc ion batteries (ZIBs) have aroused the wide interest of researchers. Especially the use of zinc metal as an anode of ZIBs has a higher theoretical capacity and simplifies the battery manufacturing process. However, serious problems happen at the electrode/electrolyte interface, such as dendrite growth and side reactions, making the coulombic efficiency and lifetime of Zn-metal electrodes far from satisfactory. It aroused the interest of researchers in seeking various additives to solve those above problems. For the rapid development of electrolyte additives in this new field, it is necessary to provide theoretical support. The electroplating of zinc metal has been developed for nearly two centuries. A rich theoretical basis and various efficient electroplating additives have been developed to improve the structure and properties. Furthermore, the essence of conventional electroplating and Zn plating for ZIBs is parallel. Recent research papers also reported some new applications of electroplating additives in ZIBs. This review starts from the basic theory of electroplating and relates the application of electroplating additives in reversible ZIBs. The basic and new understanding of traditional electroplating additives applied to high-performance ZIBs (including the mechanism of action, additive types, and technical challenges) is summarized, providing guidance for accurate evaluation and analysis of high-efficiency ZIBs electrolyte additives in the near future.
Connection of Bipolar Plate with Graphite Felt Electrode for Vanadium Flow Battery Using a Powder Thermal Unification Method
Authors: Nambi Krishnan N. , Gupta Gaurav , Satola Barbara , Uhlig Lisa M. , Germer Wiebke , Zobel Marco
Published: September 2022

Carbon felt electrodes are usually compressed against the bipolar plates in order to decrease the contact resistance, but it leads to high pressure drop and consumption of pumping energy in conventional vanadium redox flow battery stacks. This paper describes the fabrication of an effective way to unify the bipolar plate and graphite felt electrode in order to improve the battery efficiency at lower felt compression pressure. The unification process involves a thermal fusion technique with a component design consisting of bipolar plate, graphite felt electrode and connecting powder. The powder comprises either polyvinylidene difluoride or a mixture of polyvinylidene difluoride and conductive carbon black. The interfacial bonding substance determines the electrical resistance of the resultant fabricated unified assembly. The electrical resistance results prove that the carbon black proportion in the bonding element substantially reduces the electrical resistance. The optimum quantity of carbon black in the powder is found to be 40 wt%. Micro-computed tomography analysis findings indicate that thermally unified assembly interfacial contact electrode porosity is slightly lower than that of an unbonded sample. A two-cell vanadium redox flow battery stack with integrated unified assembly achieves a rather constant energy efficiency of 76% during 100 cycles with 5% electrode compression at a current density of 80 mA cm−2.
Electrochemical Nucleation and Growth of Cobalt after Leaching Waste Lithium-Ion Batteries Using a Deep Eutectic Solvent
Authors: Aldana-González J. , Sampayo-Garrido A. , Hernández-Pérez D. , de Oca-Yemha M. G. Montes , Arce-Estrada E. M. , Ramírez-Silva M. T. , Morales-Gil P. , Romero-Romo M. , Mugica-Álvarez V. , Palomar-Pardavé M.
Published: September 2022

The present work deals with the nucleation and growth process of metallic cobalt clusters onto glassy carbon, and the development of an environmentally friendly recycling process for the recovery of cobalt as a value-added product from spent lithium-ion batteries (LiBs), using a deep eutectic solvent, DES, formed by choline chloride and urea, termed reline. It was shown that reline works as leaching medium to extract Co(II) from cathode powders of dismantled spent batteries, thereby obtaining, after doing the electrodeposition process using the same reline as operating bath, a solid Co metal phase onto a glassy carbon electrode. Finally, supplementary relevant characterization of the deposits formed was carried out by means of scanning electron microscopy, energy-dispersive X-ray spectroscopy and X-rays photoelectrons spectroscopy, XPS.
Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments
Authors: C R Komala , Vimal S. , Ravindra G. , Hariramakrishnan P. , Razia Shaik , Geerthik S. , Raja K. , Mohanavel V. , Arappali Nedumaran
Published: September 2022

The outer surface of the building is the same size as its premises, with greater heat loss. Therefore, when building, renovating, or expanding apartment, if possible, avoid all kinds of spaces, ledges, and lodges in the walls. It makes sense to build unheated exterior buildings on the north side of the apartment. The storage rooms for garden tools and bicycles, technical buildings protect the warm part of the house from wind and cold. In the most common design of a private apartment, the energy consumption for heating is 110-130 kW per 1 m2 per year. In this paper, an energy distribution model was proposed to estimate the photo energy with the help of deep learning model. A small apartment not only uses less energy but also requires lower construction costs. An energy-efficient apartment is a building with a low-energy consumption and comfortable microclimate. Energy savings in such homes can be up to 90%. Annual heat demand can be less than 15 kWh per square meter of energy-efficient home.
RBM24 Mediates Lymph Node Metastasis and Epithelial-Mesenchymal Transition in Human Hypopharyngeal Squamous Cell Carcinoma by Regulating Twist1
Authors: Liu Yuhong , Pan Min , Lu Tao , Li Yanshi , Yu Dan , Wang Zhihai , Hu Guohua
Published: September 2022

Objective. Despite the target RNA regulatory action of RBM24 (RNA Binding Motif 24), a protein implicated in multiple carcinomas, its role in HSCC remains unclear. Our study probed to understand the effect of RBM24 on HSCC. Materials and Methods. A combination of qRT-PCR, IHC, and western blot was employed to assess the HSCC tissue level of RBM24. The colony formation and CCK-8 assays were performed to estimate cellular proliferative potential, whereas the transwell assay was conducted to examine invasive and metastatic potential. The FaDu cell motility was assessed via the scratch-wound assay and EMT (epithelial-mesenchymal transition) by adopting qRT-PCR in conjunction with western blot and IF (immunofluorescence). The in-vivo effect of RBM24 on HSCC was investigated through modeling metastasis to the popliteal LNs (lymph nodes). Results. Among HSCC patients showing metastasis to LNs, prominent RBM24 downregulation was noted, with an intrinsic association between low RBM24 level and poor outcome. Knocking down RBM24 promoted cell multiplication, migration, and infiltration, while overexpression led to the opposite effects and inhibited the EMT. RBM24’s suppressive action against the FaDu cell mobility and invasion was reversed by Twist1 overexpression. RBM24’s suppressive actions against the tumor evolution and LN metastasis in HSCC in-vivo were also validated. Conclusion. As a carcinoma inhibitor gene, RBM24 regulates Twist1 to achieve LN metastasis and EMT suppression in HSCC.
Recurrent Neural Model to Analyze the Effect of Physical Training and Treatment in Relation to Sports Injuries
Authors: Dhanke Jyoti A. , Maurya Rajesh Kumar , Navaneethan S. , Mavaluru Dinesh , Nuhmani Shibili , Mishra Nilamadhab , Venugopal Ellappan
Published: September 2022

Artificial intelligence has rapidly grown and has made the scenario that no field can function without it. Like every field, it also plays a vital role in the sports field nowadays. In certain sports, injuries happen very often due to heavy training and sudden speedy actions, especially in athletics and football. Here arises a need to analyze the effect of physical training in sportsperson by collecting data from their daily training. With the help of artificial intelligence, a recurrent neural model is developed to analyze the effect of physical training and treatment concerning sports injury. A Recurrent Neural Network (RNN) can be a subsection of Artificial Neural Networks (ANN) that uses the neural nodes connected in a temporal sequence. The temporal sequence is one of the essential terms in this research, which denotes a data sequence of events in a given timeframe. The recurrent neural model is an intelligent machine learning method that comprises a neural schema replicating humans. This neural schema studies the data it collects from the athletes/players and processes it by analyzing previous injuries. Sports injuries have to be analyzed because, in some cases, it becomes more dangerous to the sportsperson that they may even lose their career due to disability. Sometimes it may cause a massive loss to the club or company that hired the sportsperson for the sport. The prediction process can give the player rest until he recovers, thus becoming the safest approach in sports. Therefore, it is essential to analyze the sportsperson’s track data to keep an eye on his health. In this research, RNN model is compared with the existing Support Vector Machine (SVM) in concerning to the effect of physical training and treatment for sports. The results show that the proposed model has achieved 99% accuracy, which is higher than the existing algorithm.
Determination of Evidence Weights Based on Convolutional Neural Network for Classification Problem
Authors: Xu Shijun , Hou Yi , Deng Xinpu , Chen Peibo , Zhou Shilin
Published: September 2022

The weighted average is an efficient way to address conflicting evidence combination in the Dempster-Shafer evidence theory. However, it is an open issue how to determine the evidence weights reasonably. Although many traditional conflicting evidence combination solutions based on evidence distance or entropy have been put forward, the evidence weights are determined with a single aspect, and no comprehensive consideration of other useful information affects the weights. Thus, it does not ensure that determination of weights is the most reasonable. By introducing deep learning into conflicting evidence combination, this paper proposes a comprehensive method for determining the evidence weights based on a convolutional neural network. Taking the evidence as the network input and the corresponding weight as the output, it utilizes convolutional neural network to fully mine potentially useful information that affects the evidence weights, in order to determine the weights comprehensively. Additionally, we define a weight loss function. The weights are continuously optimized through back propagation and achieve the optimal when the weight loss function value is the minimum. Classification experimental results demonstrate that the proposed method outperforms traditional ones based on evidence distance or entropy and can be flexibly extended to other application fields as a decision-making fusion method.
Low Complement Factor H-Related 3 (CFHR3) Expression Indicates Poor Prognosis and Immune Regulation in Cholangiocarcinoma
Authors: Wang Haoran , He Meng , Zhang Zheng , Yin Wenze , Ren Bixuan , Lin Yujia
Published: September 2022

Background. Cholangiocarcinoma (CCA) is a cancerous tumor that leads to a high rate of morbidity and death. Complement factor H-related 3 (CFHR3) is a gene belonging to the CFHR gene family. In this study, we investigated the usefulness of CFHR3 in the diagnostic stage and CCA prognosis prediction. In the interim, we looked at its coexpressed genes and their roles. The correlation between CFHR3 and immunological infiltration was also investigated. Methods. The expression of the genes data and the clinical information were obtained from the databases of The Cancer Genome Atlas (TCGA) together with the Gene Expression Omnibus (GEO). The crucial gene was found to be the overlapping gene in the two databases. The area under the curve (AUC) and the Kaplan-Meier survival curve were used to describe the usefulness of the predictive prognosis of CCA patients. Univariate regression analysis and multivariate survival analysis were performed to find the independent prognosis factors. The PPI network was constructed based on the STRING database, and the coexpression approach was utilized in predicting the coexpression genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were also performed to identify the related functions. Additionally, the probable mechanism of the important gene was examined using gene set enrichment analysis (GSEA). The correlation between CFHR3 and immune infiltration was discovered using TIMER. The LncACTdb 3.0 database was used to analyze the location of CFHR3 in the cell. The cBioPortal database was used to find the mutation in CFHR3. Results. TCGA datasets and GEO datasets revealed an elevated expression level of CFHR3 in normal tissues as well as a lower expression level in cholangiocarcinoma tissues in the present research. The low expression level of CFHR3 was related to an unfavorable prognosis. Using CFHR3 expression in diagnosis and predicting the patient prognosis (

AUC
=
1.000

) is valuable. Using the CFHR3 gene and a time-lapse prediction, we could estimate survival rates over 1, 2, and 3 years. The AUC values were more than 0.6(

AUC
=
0.808
;
0.760
;
0.711

). Functional enrichment analysis revealed a substantial correlation between this signature and complement and coagulation cascades. The same outcomes from GSEA were achieved. We found the key gene widely exists in the nucleus, exosomes, and cytoplasm of normal cells using the LncACTdb 3.0 database. In immune regulation analysis, we identified that the expression level of CFHR3 had a positive correlation with infiltrating levels of B cells, neutrophils, and macrophages, but correlated negatively with cholangiocarcinoma cells, CD8+ T cells, and monocytes.
NEK2 Serves as a Novel Biomarker and Enhances the Tumorigenicity of Clear-CellRenal-Cell Carcinoma by Activating WNT/β-Catenin Pathway
Authors: Zhou Jiancheng , Lai Jiawei , Cheng Yongyi , Qu Weixing
Published: September 2022

Objective. Currently, cumulative evidence has shown that loss of NEK2 function suppresses tumor growth. However, complete studies on the regulatory role of NEK2 in clear-cellrenal-cell carcinoma (ccRCC) are rarely reported. Methods. The GEPIA database was used for information mining to analyze the gene expression differences between ccRCC tumor and normal tissues. At the same time, we analyzed the protein expression of NEK2 in clinical ccRCC samples and ccRCC cell lines. We detected the effect of NEK2 on the biological behavior of ccRCC at the cell level and further verified the biological effect of NEK2 on ccRCC cells in vivo by nude mouse tumorigenesis experiment. The expression of WNT/β-cateninpathway-related proteins and downstream proteins related to cell function were detected by Western blotting. Results. Using the GEPIA database, we observed that NEK2 expression level in ccRCC tissues was significantly higher than that in normal kidney tissues and was also related to tumor grade. The survival time of patients with ccRCC with high NEK2 expression was shorter than that of patients with low NEK2 expression. Compared with adjacent carcinoma and normal renal tubular epithelial cells, NEK2 levels were highly expressed in ccRCC tissues and ccRCC cell lines. NEK2 interference restrained ccRCC cell growth, migration, and invasion. NEK2 regulated the malignant behavior of ccRCC cells through the WNT/β-catenin pathway. Nude mouse tumorigenesis assay results showed that the transplanted tumors from NEK2 silenced mice grew more slowly and were smaller in size than those from control mice. Conclusions. NEK2 elevation may be associated with poor prognosis in ccRCC, and NEK2 enhances ccRCC cell proliferation, migration, and invasion ability by activating the WNT/β-catenin signaling pathway.
Performance Evaluation Method of Public Administration Department Based on Improved DEA Algorithm
Authors: Guan Qing , Zou Shuilong , Liu Hong , Chen Qing
Published: September 2022

This paper proposes a performance evaluation method of public administration departments based on the improved DEA algorithm, which solves the quality problem of performance evaluation of public administration departments and lays a foundation for the long-term development and performance improvement of public administration departments. The DEA model is the core to sort out the performance evaluation methods of public administration departments. From the perspective of DEA algorithm, whether DEA is effective is an important content that public administration departments must consider when carrying out performance administration, and public service satisfaction is the core parameter obtained by DEA algorithm. That is to say, by optimizing public services and improving service satisfaction, the public administration department can further improve the quality of performance evaluation. Therefore, we can carry out performance evaluation of public administration departments from the satisfaction of public services. The empirical research conclusion shows that according to the effective judgment theorem of DEA, it can be concluded that among the eight social security departments, there are five departments that can achieve DEA effectiveness, namely department 2, department 3, department 4, department 5, and department 6. There are three non-DEA valid ones, namely, department 1, department 7 and department 8. The public satisfaction and the total service cost will affect the performance quality to a certain extent, and only by balancing various influencing factors can the performance evaluation quality of the public administration department be maximized.
Research on Athlete Detection Method Based on Visual Image and Artificial Intelligence System
Authors: Wang Weiyi
Published: September 2022

Pedestrian detection and tracking based on computer vision has gradually become an international pattern recognition, which is one of the most active research topics in the field of computer vision and artificial intelligence. Using the theoretical results in the field of pattern recognition and computer vision technology, we are committed to detect and track pedestrians from video sequences. In addition to computer vision-based passer-by detection and tracking technology as the key, in the advanced computer vision action and analysis, it has a direct impact on the accuracy and robustness of its understanding. We analyzed various targets, such as subsequent recognition motion and pedestrian motion, and described them as high-level application processing, such as action understanding. In addition, because of the unique texture of human clothes compared with the surrounding natural landscape, they are highly “prominent” from the perspective of human visual system, and they are particularly prominent in the peripheral part of human contact with the background. In this paper, a binary function based on importance is proposed. As the space representation of image itself is not sensitive to noise and local signal, space representation is used. In addition, as an observation model, it can reduce the adverse effects of background noise and local noise on the tracking algorithm. Through the function block tracking, the pedestrian’s body can be tracked in detail. At the same time, the color band learning method is used to update the target template online to deal with the changes of target appearance caused by sunshine, pedestrian posture, and other factors. According to the experimental results, even if the appearance and posture of pedestrians change greatly, it has a stable tracking effect.
Image Semantic Recognition and Segmentation Algorithm of Colorimetric Sensor Array Based on Deep Convolutional Neural Network
Authors: Tang Jingjing , Wang Li , Huang Jing , Shi Aiye , Xu Lizhong
Published: September 2022

Semantic feature recognition in colour images is required for identifying uneven patterns in object detection and classification. The semantic features are identified by segmenting the colorimetric sensor array features through machine learning paradigms. Semantic segmentation is a method for identifying distinct elements in an image. This can be considered a task involving image classification at the pixel level. This article introduces a semantic feature-dependent array segmentation method (SFASM) to improve recognition accuracy due to irregular semantics. The proposed method incorporates a deep convolutional neural network for detecting the semantic and un-semantic features based on sensor array representations. The colour distributions per array are identified for horizontal and vertical semantics analysis. In this analysis, deep learning classifies the uneven patterns based on colour distribution, i.e. the consecutive and scattered colour distribution pixels in an array are correlated for their similarity. This similarity identification is maximized through max-pooling and recurrent iterations, preventing detection errors. The proposed method classifies the semantic features for further correlation sections, improving the accuracy. The proposed method’s performance is thus validated using the metrics precision, analysis time and F1-Score.
[Retracted] A Comprehensive Review of Performance of Next‐Generation Sequencing Platforms
Authors: Pervez Muhammad Tariq , Hasnain Mirza Jawad ul , Abbas Syed Hassan , Moustafa Mahmoud F. , Aslam Naeem , Shah Syed Shah Muhammad
Published: September 2022

Background. Next‐generation sequencing methods have been developed and proposed to investigate any query in genomics or clinical activity involving DNA. Technical advancement in these sequencing methods has enhanced sequencing volume to several billion nucleotides within a very short time and low cost. During the last few years, the usage of the latest DNA sequencing platforms in a large number of research projects helped to improve the sequencing methods and technologies, thus enabling a wide variety of research/review publications and applications of sequencing technologies. Objective. The proposed study is aimed at highlighting the most fast and accurate NGS instruments developed by various companies by comparing output per hour, quality of the reads, maximum read length, reads per run, and their applications in various domains. This will help research institutions and biological/clinical laboratories to choose the sequencing instrument best suited to their environment. The end users will have a general overview about the history of the sequencing technologies, latest developments, and improvements made in the sequencing technologies till now. Results. The proposed study, based on previous studies and manufacturers’ descriptions, highlighted that in terms of output per hour, Nanopore PromethION outperformed all sequencers. BGI was on the second position, and Illumina was on the third position. Conclusion. The proposed study investigated various sequencing instruments and highlighted that, overall, Nanopore PromethION is the fastest sequencing approach. BGI and Nanopore can beat Illumina, which is currently the most popular sequencing company. With respect to quality, Ion Torrent NGS instruments are on the top of the list, Illumina is on the second position, and BGI DNB is on the third position. Secondly, memory‐ and time‐saving algorithms and databases need to be developed to analyze data produced by the 3rd‐ and 4th‐generation sequencing methods. This study will help people to adopt the best suited sequencing platform for their research work, clinical or diagnostic activities.