bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonwetting Effects of Si Contamination on Cu Bumps of a Flip Chip Package—A Case Study
Authors: Salamania Janella Mae R.
Published: December 2020

Presence of foreign materials (i.e, contamination) can affect the reliability of copper (Cu) bumps when it affects the wettability of the solder and consequently weakens the joint formation of the copper to the substrate. This paper looks at a case of non-wetting of Cu bumps due to silicon contamination induced during assembly processing. In this case study, surface roughness is the main factor being altered when foreign materials contaminate the metal substrate. Sample devices were tested in a resistive open unit and a direct current failing unit, respectively. It was found that the silicon dust present on the substrate in effect "roughens" the surface, thereby decreasing the wettability between the molten solder to the metal substrate. For future studies, it is recommended that the effect of reliability stress activities on the Cu bumps with silicon contaminations be examined to evaluate the risks for possible field failures of this defect.
Application of Electro Optical Terahertz Pulse Reflectometry for Fault Localization and Defect Analysis
Authors: Lin Yi-Sheng , Hsiao Yu-Hsiang , Lee Shu-Hua
Published: December 2020

Electro Optical Terahertz Pulse Reflectometry (EOTPR) is an E-FA (Electrical Failure Analysis) technique in the semiconductor industry for non-destructive electrical fault isolation for shorts, leakages and opens. This paper introduces the capability and presents several case studies identifying the physical location of defects where EOTPR is useful as a non-destructive analysis technique. In this paper, the methodology and application of EOTPR on open and short failure isolations in advanced 2.5D IC and wafer level packages (WLP) have been presented. The experimental results of P-FA (Physical Failure Analysis) verify the accuracy of the EOTPR system in determining the distance to defect.
A Study on the Cause and Improvement Method of Aluminum PAD Disappearance Defect in TSV Package Process
Authors: Kim Boem-Su , Park Su Hyeon , Kim Hyoung Ryeun , Hwang Sung Min
Published: December 2020

Through Silicon Via (TSV) Package (PKG) technology that forms a 3D stack with chip to chip or wafer to wafer contact, uses a variety of wet chemicals unlike conventional package technology. Therefore, new kinds of defects related to the wet chemical occur. In this a new failure mode of disappeared Al pad will be presented, a problem came up to disappear Al pad, which served as the fiducial key during the metal residue removal process after forming the TSV PKG front bump, the mechanism of disappearance of Al pad was investigated. Through chemical analysis of process and equipment, we found that Cu etchant (including H3PO4) can damage for Al pad. The process simulation demonstrated that Al pad actually disappeared. Therefore, it confirmed that it needs to be removed through sufficient rinsing time after applying the wet chemical applied to the TSV PKG process. As a result we solved problem through modified equipment and increased rinsing time.
Device Channel Temperature Measurement Using NIR Emission
Authors: Weger Alan J. , Stellari Franco , Song Peilin
Published: December 2020

In this paper, we present a technique for device temperature measurement using spontaneous near infrared (NIR) emission from an Integrated Circuit (IC). By leveraging modeling and data analysis, time-integrated emission measurements are used to estimate the temperature increase due to switching activity inside the channel of CMOS transistors. The non-invasive nature of the technique allows one to reliably monitor the temperature of any device on-chip without the need for circuit modifications or dedicated on-chip sensors and with a higher spatial resolution than thermal cameras. This method has important applications for modeling heat dissipation during early process development, localizing hot spots, calibrating on-chip sensors, etc. In this paper, temperature is estimated by fitting empirical emission data to an emission model that can be solved for device channel temperature.
Picosecond Time-Resolved LADA Integrated with a Solid Immersion Lens on a Laser Scanning Microscope
Authors: Dickson Kris , Erington Kent , Bodoh Dan , Serrels Keith , Petri Charles , Ybarra Juan , Ly Khiem
Published: December 2020

We present an upgraded time-resolved LADA system, with a 25ps pulsed laser, integrated into a commercial laser scanning microscope used in failure analysis. We demonstrate the use of this system on 14nm/16nm finfet devices.
Ion Milling of Ex-Situ Lift-Out FIB Specimens
Authors: Campin M.J. , Bonifacio C.S. , Boccabella M. , Fischione P.E. , Kang H.H.
Published: December 2020

The semiconductor industry is constantly investigating new methods that can improve both the quality of TEM lamella and the speed at which they can be created. To improve throughput, a combination of FIB-based preparation and ex situ lift-out (EXLO) techniques have been used. Unfortunately, the carbon support on the EXLO grid presents problems if the lamella needs to be thinned once it is on the grid. In this paper, we present low-energy (<1 keV), narrow-beam (<1 μm diameter), Ar+ ion milling as a method of preparing electron-transparent and gallium-free EXLO FIB specimens.
Increasing FA Throughput in Challenging Samples Utilizing TRUE X-Sectioning and the Rocking Stage
Authors: Šikula Marek , Hrnčíř Tomáš , Gounet Pascal
Published: December 2020

An advanced sample preparation protocol using Xe+ Plasma FIB for increasing FA throughput is proposed. We prepared cross-sections of 400 μm and wider in challenging samples such as a BGA (CSP), bond wires in mold compound or a TSV array. These often suffer from FIB milling artifacts. The unsatisfactory quality of the cross-section face is mainly due to extremely different milling rates of the various materials (polyimide, tin, copper, mold compound, platinum), ion beam induced ripples [1] or due to significant surface topography. We explored the usability of the protocol for standard cross-sections and also tested the preparation of TEM lamellae. The process parameters of the proposed approach were compared with the standard methods of Xe+ Plasma FIB FA with respect to preparation time and cross-section quality. Aiming for ultimate results, we incorporated the Rocking stage technique which also greatly improves cross-section quality.
Fin Level Defect Isolation Inside a FinFET Using Electron Beam Alteration of Current Flow
Authors: Ryu H.J. , Shah A.B. , Wang Y. , Chuang W.-H. , Tong T.
Published: December 2020

When failure analysis is performed on a circuit composed of FinFETs, the degree of defect isolation, in some cases, requires isolation to the fin level inside the problematic FinFET for complete understanding of root cause. This work shows successful application of electron beam alteration of current flow combined with nanoprobing for precise isolation of a defect down to fin level. To understand the mechanism of the leakage, transmission electron microscopy (TEM) slice was made along the leaky drain contact (perpendicular to fin direction) by focused ion beam thinning and lift-out. TEM image shows contact and fin. Stacking fault was found in the body of the silicon fin highlighted by the technique described in this paper.
Advanced In Situ X-ray Metrology for Thermal Interface Materials Package Failure Analysis
Authors: Li Peng , Mar Alfred La , Liu Yongmei , Goyal Deepak
Published: December 2020

Innovative in situ X-ray metrologies for package failure analysis (FA) were developed to understand solder thermal interface materials (STIM) package process and failure mechanisms through elevated temperature. Dynamic STIM void formation mechanism and STIM bleeding-out dependency on reflow were observed. It was found that long sit time before STIM liquidus temperature helps to minimize the STIM void formation and fast cooling mitigates the STIM bleed-out risk. Our studies demonstrate that in situ metrologies offer direct guidance to packaging process optimization and accelerate root-cause identification for temperature induced package failures; therefore, it improves throughput-time for packaging technology development.
Sample Preparation Techniques for Reduced Lateral Heat Distribution and Implications for Non-IR Probing on Integrated Circuits
Authors: Mulholland Matthew M. , Vlasyuk Vladimir V. , Wadell Robert P. , Khan Imran , Bakken Nathan J.
Published: December 2020

Validation techniques on packaged integrated circuit (IC) samples positively impact time to market (TTM) by saving considerable fabrication modification turnaround time and costs. The validation techniques are typically done by working through the backside of the chip. These validation and debug techniques, such as optical probing, use the Solid Immersion Lens (SIL) for imaging and data collection. Solid Immersion Lens based near infrared (NIR) optical probing systems have been an integral function in the product life cycle enabling a fast, reliable, and low defect product to market. For the SIL configuration, the remaining silicon thickness (RST) target is specified to be 50 +/- 5um. The sample preparation tools and techniques to accomplish this have been fully developed and matured enough to provide this specification for all segment form factors. This silicon thickness is also within a sustainable thermal envelope at certain power densities during debug electrical testing and validation. As we move into the next generation of optical probing debug in the visible range, increasing resolution further, new sample preparation methods need to be developed. There are a number of different strategies and techniques to prepare the sample, while also enabling efficient heat transfer. This paper will detail some of the sample preparation techniques as a function of silicon thickness and aspect ratio. These final geometries will then be characterized thermally by investigating lateral heat distribution and junction temperature within the silicon Region of Interest (ROI). Finally, based on this sample preparation and thermal study, implications around debug techniques for optical probing will be discussed.
Measurement of Dielectric Constant and Doping Concentration of a Cross-Sectioned Device by Quantitative Scanning Microwave Impedance Microscopy
Authors: Iyer D. , Messinger A. , Crowder R. , Zhang Y. , Amster O. , Friedman S. , Yang Y. , Stanke F.
Published: December 2020

Scanning microwave impedance microscopy (sMIM) is an emerging technique that can provide detailed information beyond that of conventional scanning capacitance microscopy (SCM), and other electrical scanning probe microscopy (SPM) techniques, for the investigation and failure analysis (FA) of semiconductor devices. Integration of new dielectric materials at lower levels of the device structure with the need for quantification of dielectric and dopants in semiconductor devices with sub-micron spatial resolution pushes the practical boundaries of typical atomic force microscopy (AFM) electrical modes. sMIM can measure both linear and non-linear materials (insulators and doped semiconductors, respectively) simultaneously. sMIM has a linear response to log k (dielectric number) and log N (doping concentration) making it an ideal method for providing quantitative measurements of semiconductor devices over a large range of values. This work demonstrates an example of a practical application of sMIM for quantitative measurement of the dopant concentration profile in production semiconductor devices. A planar dopant calibration sample is used to calibrate the sMIM prior to performing the measurements on an “unknown” production device. We utilize nanoscale C-V data to establish a calibration curve for both n- and p-type carriers and apply the calibration curve to an “unknown” device, presenting the measurements in units of doping concentration.
Advanced T-LSIM System Detections using Amplified External Isolated Source-Sense Unit
Authors: Lau Zhi Jie , Philips Chris
Published: December 2020

Thermal-Laser Signal Injection Microscopy (T-LSIM) is a widely used fault isolation technique. Although there are several T-LSIM systems on the market, each is limited in terms of the voltage and current it can produce. In this paper, the authors explain how they incorporated an Amplified External Isolated Source-Sense (AxISS) unit into their T-LSIM platform, increasing its current sourcing capability and voltage biasing range. They also provide examples highlighting the types of faults and failures that the modified system can detect.
FIB-Based Sample Preparation for Localized SCM and SSRM
Authors: Lorut Frédéric , Valéry Alexia , Chevalier Nicolas , Mariolle Denis
Published: December 2020

Dopants imaging using scanning capacitance microscopy (SCM) and scanning spreading resistance microscopy are used for identifying doped areas within a device, the latter being analyzed either in a top view or in a side view. This paper presents a sample preparation workflow based on focused ion beam (FIB) use. A discussion is then conducted to assess advantages of the method and factors to monitor vigilantly. Dealing with FIB machining, any sample preparation geometry can be achieved, as it is for transmission electron microscopy (TEM) sample preparation: cross-section, planar, or inverted TEM preparation. This may pave the way to novel SCM imaging opportunities. As FIB milling generates a parasitic gallium implanted layer, a mechanical polishing step is needed to clean the specimen prior to SCM imaging. Efforts can be conducted to reduce the thickness of this layer, by reducing the acceleration voltage of the incident gallium ions, to ease sample cleaning.
OBIRCH for Isolating High and Low Resistance Test Structure Failures During Sub-14nm Technology Development
Authors: Masnik John , Saujauddin Noor Jehan , Davidson Kevin , Chen Esther P.Y. , Beaudoin Felix
Published: December 2020

OBIRCH is a static technique for isolating both high and low resistance failures in test structures that continues to be relevant to sub 14nm technologies. While limited resolution is a factor as devices get smaller, an approximate location is adequate for finding obvious defects on sub 14nm technology structures. Its speed is what makes this technique appealing. If the approximate location isn’t good enough, a more time-consuming, higher-resolution technique can be employed. But the use of OBIRCH as a first isolation technique saves considerable time for a high volume FA lab if obvious defects cause the majority of failures. The seven case studies on sub 14nm technology are examples of obvious defects where OBIRCH had adequate resolution for isolation. The OBIRCH results for the first example are compared to the PVC (Passive Voltage Contrast) and EBAC (Electron-Beam Absorbed Current Imaging) findings to illustrate each technique’s strength and weakness.
Mitigation of Dielectric Charging in MEMS Capacitive Switches with Stacked TiO2/Y2O3 Insulator Film
Authors: Birmpiliotis D. , Koutsoureli M. , Buhagier L. , Papaioannou G. , Ziaei A.
Published: December 2020

Metal-insulator-metal (MIM) capacitors with single TiO2 and a TiO2/Y2O3 stack are used as insulator films in MIM and MEMS, respectively, are explored. It is found that, under electron injection from bottom electrode, the TiO2 MIM capacitors demonstrate resistive switching with a magnitude of leakage currents not usable for MEMS application. The deposition of a stacked TiO2/Y2O3 dielectric film improves the MEMS performance without compromising the low dielectric charging of TiO2 single layer.
Identifying the Root Cause of Source-Drain Leakage Caused Soft Fail in Advanced Bulk FinFET Devices
Authors: Chen Liangshan , Wei Yuting , Schaeffer Tanya , Oh Chongkhiam
Published: December 2020

The paper reports the investigation on the root cause of source-drain leakage in bulk FinFET devices. While the failing device was readily isolated by nanoprobing technique and the electrical analysis pinpointed the potential defect location inside the Fin channel, the identification of physical root cause went through extreme challenges imposed by the tiny-sized device and the unique FinFET 3D architecture. The initial TEM analysis was misled by the projection of a species in the lamella surface and thus could not explain the electrical data. Careful analysis on the device structure was able to identify the origin of the species and led to the discovery of the actual root cause. This paper will provide the analysis details leading to the findings, and highlight the role of electrical understanding in not only providing guidance for physical analysis but also revealing the true root cause of failure in FinFET devices.
Nanoprobing and EBAC for Improving Failure Analysis Success Rates on Sub-14nm Logic and SRAM
Authors: Masnik John , Saujauddin Noor Jehan , Davidson Kevin , Chen Esther P.Y.
Published: December 2020

Nanoprobing, electrical probing (DC electrical measurement of semiconductors using nanoscale probes) on an electron microscopic scale, and EBAC, a high-resolution, static technique, can be used for isolating defects and improving failure analysis success rates on both logic and SRAM devices. This paper presents three case studies of subtle defects on a technology beyond 14nm that required nanoprobing.
A Method to Enhance the Front-Side Lapping Process for Localisation of Sub-Surface Defect for Advanced Packages
Authors: Tan Sze Yee , Wong Chiu Soon , Lo Chea Wee , Goh Cin Sheng
Published: December 2020

In the back-end assembly process, all of the packages will be tested prior to disposition to the customers in order to filter out any device with failure. For a reject unit with an unknown failure mechanism, it will be subjected to a comprehensive failure analysis (FA) to identify the root cause of the failure. Non-destructive verification, following by front-side decapsulation and internal physical inspection is the common way to visualise and identify the physical defect that usually causes the failure of a device during the back-end assembly process. For certain failures, visualization of the defect might not be straight forward after the decapsulation because the defect may be embedded or buried underneath a layer or wedge bond on the die. In this case, a more complicated FA analysis flow which comprises various precision techniques such as parallel lapping, hotspot localisation and focused-ion-beam (FIB) analyses will be needed to thin down the top layer/wedge bond for a precise localisation of the defect prior to precision analysis by FIB. However, the process to thin down the top layer/wedge bond with an exposed die of a partially decapsulated package is a tricky job as artefacts such as crack/scratches on die are likely to be introduced during the process of polishing. Also it is relatively difficult to control the thickness and levelling of the top layer/wedge bond during the thinning process. In this work, we developed a method that allows the analyst to re-cap the partially decapped package, and also to precisely measure and thin down the top layer to an accuracy of less than < 2um without the introduction of artefacts.
Dynamic Photon Emission on FinFET Devices Through Novel Scan Test Approaches
Authors: Gopinath Ranganathan , Venkat Krishnan Ravikumar , Winson Lua , Angeline Phoa , Jie Jin
Published: December 2020

Dynamic Photon Emission Microscopy (D-PEM) is an established technique for isolating short and open failures, where photons emitted by transistors are collected by sensitive infra-red detectors while the device under test is electrically exercised with automated test equipment (ATE). Common tests, such as scan, use patterns that are generated through Automatic Test Pattern Generator (ATPG) in compressed mode. When these patterns are looped for D-PEM, it results in indeterministic states within cells during the load or unload sequences, making interpretation of emission challenging. Moreover, photons are emitted with lower probability and lesser energies for smaller technology nodes such as the FinFET. In this paper, we will discuss executing scan tests in manners that can be used to bring out emission which did not show up in conventional test loops.
Analysis of Voltage Contrast in Secondary Electron Images Using a High-Energy Electron Spectrometer
Authors: Asano Natsuko , Asahina Shunsuke , Erdman Natasha
Published: December 2020

Voltage contrast (VC) observation using a scanning electron microscope (SEM) or a focused ion beam (FIB) is a common failure analysis technique for semiconductor devices.[1] The VC information allows understanding of failure localization issues. In general, VC images are acquired using secondary electrons (SEs) from a sample surface at an acceleration voltage of 0.8–2.0 kV in SEM. In this study, we aimed to find an optimized electron energy range for VC acquisition using Auger electron spectroscopy (AES) for quantitative understanding.
Super XHR Cross-Sectional SEM Imaging & EDS Analysis: A Systematic Method for High-Fidelity Microstructure Characterization of Dense SRAM FinFET
Authors: Kral Zdenek , Jensen Jake , McGill Lisa , Landin Trevan , Alvis Roger , Seddio Stephen M. , Stephens Chris
Published: December 2020

The potential benefits and challenges of low kV SEM imaging and EDS elemental analysis have been discussed in the SEM community since at least the early 1990s [1,2]. Concurrent with steady progress in the performance of so-called extreme high-resolution ‘XHR’ SEM imaging [3], is an advancement in low-energy EDS using windowless, large solid angle ‘racetrack’ EDS detectors [4]. As lower kV imaging and EDS analysis becomes accessible, refined models of the interaction of low energy electron beam and real-world samples continues at full speed even today [5].
Failure Analysis Approaches for Stacking Fault Defects in FinFET Devices
Authors: Kim Beomjun , Park Seonghee , Kim Juhyun , Lee Moonhyun , Cho Seongjun , Won Seokjun , Kim Jinsung
Published: December 2020

In this paper, the stacking fault defects in FinFETs are described as the root cause of the PLL failure. Failure analysis approaches such as photon emission microscopy and nano probing were applied to pinpoint the exact stacking fault location in even transistor level and High resolution TEM confirmed the stacking fault defects in the Fin which was isolated by nano probing. RX local density was confirmed as the key factor in stacking fault generation by TCAD simulation. RX new mask with dummy addition was made to mitigate stress and was confirmed to be effective to reduce the compressive strain at the channel in FinFETs by Geometric Phase Analysis (GPA) which provided sufficiently practical local strain measurement data. The GPA techniques demonstrated here are informative for process improvement and failure analysis in FinFET devices.

Keywords – Stacking Fault, Geometric Phase Analysis
Robust Test Method of TSOP PEMs for Space Application
Authors: Iwai Yasunobu , Shinozaki Koichi , Tanaka Daiki
Published: December 2020

Compared with space parts, consumer parts are highly functional, low cost, compact and lightweight. Therefore, their increased usage in space applications is expected. Prior testing and evaluation on space applicability are necessary because consumer parts do not have quality guarantees for space application [1]. However, in the conventional reliability evaluation method, the test takes a long time, and the problem is that the robustness of the target sample can’t be evaluated in a short time.

In this report, we apply to the latest TSOP PEM (Thin Small Outline Package Plastic Encapsulated Microcircuit) an evaluation method that combines preconditioning and HALT (Highly Accelerated Limit Test), which is a test method that causes failures in a short time under very severe environmental conditions. We show that this method can evaluate the robustness of TSOP PEMs including solder connections in a short time. In addition, the validity of this evaluation method for TSOP PEM is shown by comparing with the evaluation results of thermal shock test and life test, which are conventional reliability evaluation methods.
Deep drawing of a stellar shape using finite element simulation and experimental
Authors: Khalid Jawad Waleed , T. Ikal Ali
Published: December 2020

The process of deep drawing of complex shapes is a difficult process compared to the process of drawing simple shapes such as cylindrical, square and rectangle because of the complex shape is subjected to the higher stresses concentration compared to simple shapes. This work aims to study the effect of the wall corner radius of punch and radial clearance on deep drawing operation using the experimental work and numerical simulation. In this work, an analysis of the deep drawing process is performed for process design of stellar cup drawing. A deep drawing die was designed and manufacturing to perform the experimental procedure required to produce a stellar cup with inner dimensions (major axis equal to 43.7 mm and minor axis equal to 36.64 mm) formed from a circular flat sheet (80 mm diameter) comprised of low carbon steel of (0.08%) carbon content, without any intermediate annealing. A commercially finite element program code (ANSYS 18.0) is utilized to simulate the stellar deep drawing operation. From the comparison between the results, it has been found that the thinning at cup corner increases by decreasing the wall corner radius of the punch and the maximum thinning with the wall corner radius of the punch equal to ( 16Rcp'>  = 2 mm) at the corner of the minor axis of completely drawn cup
ZEYBEK MÜZİĞİNİN ZAMANSAL, TEMPO VE BİREŞİM DEĞERLENDİRMESİ
Authors: ERKAN Tarkan
Published: December 2020

Batı Anadolu’da, geçmişte haksızlığa uğrayanın yanında olan zeybekler, özellikle Millî Mücadele yıllarında vatanın özgürlüğü için savaşmalarıyla, halkın sevgilisi haline gelmiş, halk her yerde her ortamda ve her şekilde zeybeklerin yanında olmuş, onlara sıkı sıkı sarılmış ve bağlanmışlardır. Halk, bu duygu, düşünce ve anlayışla, zeybeklere takdir ve hayranlıklarını içeren türküler yakmışlardır. Bu sebeple zeybekliğe ithaf edilen hatta zeybeklik kurumunun içerisinden çıkan müziklerin; kahramanlık, savaş, hasret, sevgi, ayrılık, üzüntü gibi konular üzerine kurulduğu bilinmektedir. Bu yakılan türkülerin kültürel değerleri vardır ve gelecek nesillere aktarımı, eksiksiz, net bir şekilde sağlanmalıdır. Buradan yola çıkarak; ezgileri notalayan kişilerin veya kurumların, müzik ölçülerinin zaman tespitinde veya birim değer tespitlerinde yeteri kadar özenli davranmadığı saptanmıştır. Eski alışkanlıklara göre konulmuş birim değerler veya zamanlar ile notalama yapılmamalıdır. Notalar, hız ile belirlenen birim değerlere göre yazılmalıdırlar. Ayrıca, 27 zamanlı ölçülerin, 9 zamanlı ölçü içerisine zorlama yapılarak notaya alanların da olduğu tespit edilmiştir. Bu tür yanlışlıkların doğru algılandığı durumlarda ise karışıklık çıkması elbette kaçınılmazdır ve gelecek nesillere aktarımda karmaşaya sebep olabilecektir. Bu çalışmanın amacı; günümüze kadar gelen zeybek müzik repertuvarı içerisinde tespit ettiğimiz sorunları, bilimsel bir tabana oturmayan ezgi derlemelerini, notaya alımları ve bunların sonucunda oluşan zamansal, tempo ve bireşimsel karışıklığı gidermektir. Çalışma, bugüne kadar doğru bilinen yanlışları karşılaştırmalı yöntem kullanarak, araştırmalar sonucunda varılan zamansal, tempo ve bireşimsel özellikleri farklı örneklerle ortaya koymayı hedeflemektedir.
Interioritas Ruang Gerak Membaca Literatur Fiksi Ergodik House Of Leaves
Authors: Sulistiani Coriesta Dian , Azzahra Hanifah
Published: December 2020

Ergodic fiction literature is different from other fiction literature. Ergodic literature elements determine the space of the reader. It affects the reader to move that is not limited to the hand and eye movements, but also spatial movements of other limbs. This paper discusses the interiority that occurs behind the body space of readers of ergodic fiction literature. Through a qualitative analysis of the mapping of body space in reading the ergodic literature of Mark Z Danielewski’s House of Leaves (2000), the result shows that elements of ergodic fiction such as narration, nodes, options, multiple paths, and peritext are part of the interiority of space.
Integrative analysis of transcriptional profile reveals LINC00052 as a suppressor of breast cancer cell migration
Authors: Sanchez-Lopez Jose Manuel , Mandujano-Tinoco Edna Ayerim , Garcia-Venzor Alfredo , Lozada-Rodriguez Laura Fatima , Zampedri Cecilia , Uribe-Carvajal Salvador , Melendez-Zajgla Jorge , Maldonado Vilma , Lizarraga Floria
Published: December 2020

BACKGROUND: Long-non-coding RNAs, a class of transcripts with lengths > 200 nt, play key roles in tumour progression. Previous reports revealed that LINC00052 (long intergenic non-coding RNA 00052) was strongly downregulated during breast cancer multicellular spheroids formation and suggested a role in cell migration and oxidative metabolism. OBJECTIVE: To examine the function of LINC00052 in MCF-7 breast cancer cells. METHODS: Loss-of-function studies were performed to evaluate LINC00052 role on MCF-7 breast cancer cells. Microarray expression assays were performed to determine genes and cellular functions modified after LINC00052 knockdown. Next, the impact of LINC00052 depletion on MCF-7 cell respiration and migration was evaluated. RESULTS: 1,081 genes were differentially expressed upon LINC00052 inhibition. Gene set enrichment analysis, Gene Ontology and Key Pathway Advisor analysis showed that signalling networks related to cell migration and oxidative phosphorylation were enriched. However, whereas LINC00052 knockdown in MCF-7 cells revealed marginal difference in oxygen consumption rates when compared with control cells, LINC00052 inhibition enhanced cell migration in vitro and in vivo, as observed using a Zebrafish embryo xenotransplant model. CONCLUSION: Our data show that LINC00052 modulates MCF-7 cell migration. Genome-wide microarray experiments suggest that cancer cell migration is affected by LINC00052 through cytoskeleton modulation and Notch/β-catenin/NF-κB signalling pathways.
DEPDC1 upregulation promotes cell proliferation and predicts poor prognosis in patients with gastric cancer
Authors: Gong Zhaohua , Chu Hongjin , Chen Jian , Jiang Lixin , Gong Benjiao , Zhu Peng , Zhang Chenglin , Wang Zhixin , Zhang Wendi , Wang Jiahui , Li Chen , Zhao Huishan
Published: December 2020

BACKGROUND: Previous studies revealed that DEP domain containing 1 (DEPDC1) is involved in the carcinogenesis and progression of several types of human cancer. However the role of DEPDC1 in gastric cancer has not been studied. OBJECTIVE: The objective of this study was to study the expression and pathophysiological function of DEPDC1 in gastric cancer. METHODS: DEPDC1 expression in gastric adenocarcinoma cells was examined with Western blot and qRT-PCR. Clinical pathological features of patients were determined by immunohistochemistry. The effect of DEPDC1 expression on cell proliferation was studied by in vitro cell proliferation assay; and cell cycle influence was assessed by flow cytometry. Survival curves were plotted using Kaplan-Meier. RESULTS: DEPDC1 was overexpressed in gastric adenocarcinoma tissues compared with the paired adjacent normal gastric tissues, in accordance with mRNA level downloaded from GEPIA database. DEPDC1 expression level was significantly associated with cancer metastasis and differentiation. DEPDC1 upregulation caused cell cycle accelerating from G1 to S phase, and it was correlated with poorer overall survival. CONCLUSION: Therefore, DEPDC1 upregulation in gastric adenocarcinoma is associated with tumor development and poor clinical outcomes of the patients, implying DEPDC1 might be a potential therapeutic target against gastric cancer.
Pattern and Rule Mining for Identifying Signatures of Epileptic Patients from Clinical EEG Data
Authors: Dasgupta Abhijit , Nayak Losiana , Das Ritankar , Basu Debasis , Chandra Preetam , De Rajat K.
Published: December 2020

Epilepsy is a neurological condition of human being, mostly treated based on the patients’ seizure symptoms, often recorded over multiple visits to a health-care facility. The lengthy time-consuming process of obtaining multiple recordings creates an obstacle in detecting epileptic patients in real time. An epileptic signature validated over EEG data of multiple similar kinds of epilepsy cases will haste the decision-making process of clinicians. In this paper, we have identified EEG data derived signatures for differentiating epileptic patients from normal individuals. Here we define the signatures with the help of various machine learning techniques, viz., feature selection and classification, pattern mining, and fuzzy rule mining. These signatures will add confidence to the decision-making process for detecting epileptic patients. Moreover, we define separate signatures by incorporating few demographic features like gender and age. Such signatures may aid the clinicians with the generalized epileptic signature in case of complex decisions.
Dischargeable Obligations in the 𝒮CIFF Framework
Authors: Alberti Marco , Gavanelli Marco , Lamma Evelina , Riguzzi Fabrizio , Satoh Ken , Zese Riccardo
Published: December 2020

Abductive Logic Programming (ALP) has been proven very effective for formalizing societies of agents, commitments and norms, in particular by mapping the most common deontic operators (obligation, prohibition, permission) to abductive expectations. In our previous works, we have shown that ALP is a suitable framework for representing norms. Normative reasoning and query answering were accommodated by the same abductive proof procedure, named 𝒮CIFF. In this work, we introduce a defeasible flavour in this framework, in order to possibly discharge obligations in some scenarios. Abductive expectations can also be qualified as dischargeable, in the new, extended syntax. Both declarative and operational semantics are improved accordingly, and proof of soundness is given under syntax allowedness conditions Moreover, the dischargement itself might be proved invalid, or incoherent with the rules, due to new knowledge provided later on. In such a case, a discharged expectation might be reinstated and hold again after some evidence is given. We extend the notion of dischargement to take into consideration also the reinstatement of expectations. The expressiveness and power of the extended framework, named 𝒮CIFF𝒟, is shown by modeling and reasoning upon a fragment of the Japanese Civil Code. In particular, we consider a case study concerning manifestations of intention and their rescission (Section II of the Japanese Civil Code).
A Set-theoretic Approach to Reasoning Services for the Description Logic 𝒟 ℒ D 4,×
Authors: Cantone Domenico , Nicolosi-Asmundo Marianna , Santamaria Daniele Francesco
Published: December 2020

In this paper we consider the most common TBox and ABox reasoning services for the description logic 𝒟ℒ〈4LQSR,x〉(D) ( 𝒟 ℒ D 4,× , for short) and prove their decidability via a reduction to the satisfiability problem for the set-theoretic fragment 4LQSR. 𝒟 ℒ D 4,× is a very expressive description logic. It combines the high scalability and efficiency of rule languages such as the SemanticWeb Rule Language (SWRL) with the expressivity of description logics. In fact, among other features, it supports Boolean operations on concepts and roles, role constructs such as the product of concepts and role chains on the left-hand side of inclusion axioms, role properties such as transitivity, symmetry, reflexivity, and irreflexivity, and data types. We further provide a KE-tableau-based procedure that allows one to reason on the main TBox and ABox reasoning tasks for the description logic 𝒟 ℒ D 4,× . Our algorithm is based on a variant of the KE-tableau system for sets of universally quantified clauses, where the KE-elimination rule is generalized in such a way as to incorporate the γ-rule. The novel system, called KEγ-tableau, turns out to be an improvement of the system introduced in [1] and of standard first-order KE-tableaux [2]. Suitable benchmark test sets executed on C++ implementations of the three mentioned systems show that in several cases the performances of the KEγ-tableau-based reasoner are up to about 400% better than the ones of the other two systems.
Comparative efficiency of three gasotransmitters (nitric oxide, hydrogen sulfide and carbon monoxide): Analysis on the model of red blood cell microrheological responses
Authors: Muravyov A.V. , Tikhomirova I.A. , Avdonin P.V. , Bulaeva S.V. , Malisheva Ju.V.
Published: December 2020

BACKGROUND: It is now known regulatory effect of gaseous mediators in many bodily functions. These mediators include nitric oxide (NO), carbon monoxide (CO) and hydrogen sulfide (H2S). However, detailed data on the regulatory role of each of these gasotransmitters (GTs) are still not sufficiently studied. OBJECTIVE: The aim of this study was to investigate on models of microrheological behaviour of intact red blood cells and their recovered ghosts of cellular responses to all three known gasotransmitters: NO, H2S, and CO. METHODS: In experiments with intact red blood cells (RBCs) and their recovered ghosts (filled with an isotonic solution of known viscosity), deformability (RBCD) and aggregation (RBCA) were recorded after incubation of cells with GT donors or stimulators of their endogenous synthesis. RESULTS: It was found that all three GT donors moderately increased the deformability of both intact RBCs and their recovered ghosts (by 5–10%, p < 0.05). In addition GT donors and substrates of their endogenous synthesis significantly reduced RBCA, from 20 to 37% (p < 0.01). Experiments with inhibition of soluble guanylate cyclase (s-GC) almost completely eliminated the RBCD increasing effect of GT donors CONCLUSION: In present study it was demonstrated that all three known gaseous mediators: NO, CO and H2S cause moderate statistically significant positive alterations in RBC deformability as well as a noticeable decrease in RBC aggregation. This was confirmed both in experiments with gasotransmitter donors and stimulators of GT endogenous synthesis. In addition, the data obtained suggest that RBC microrheological responses to the actions of all three GTs are associated with activation of the guanylate cyclase signalling cascade.
Recognition of teaching method effects based on grid model simplification and artificial intelligence
Authors: Yunfeng Guo , Jing Li
Published: December 2020

In order to improve the effect of the teaching method evaluation model, based on the grid model, this paper constructs an artificial intelligence model based on the grid model. Moreover, this paper proposes a hexahedral grid structure simplification method based on weighted sorting, which comprehensively sorts the elimination order of candidate base complexes in the grid with three sets of sorting items of width, deformation and price improvement. At the same time, for the elimination order of basic complex strings, this paper also proposes a corresponding priority sorting algorithm. In addition, this paper proposes a smoothing regularization method based on the local parameterization method of the improved SLIM algorithm, which uses the regularized unit as the reference unit in the local mapping in the SLIM algorithm. Furthermore, this paper proposes an adaptive refinement method that maintains the uniformity of the grid and reduces the surface error, which can better slow down the occurrence of geometric constraints caused by insufficient number of elements in the process of grid simplification. Finally, this paper designs experiments to study the performance of the model. The research results show that the model constructed in this paper is effective.
Cross-cultural O2O English teaching based on AI emotion recognition and neural network algorithm
Authors: Zhang Mei , Zhang Lijun
Published: December 2020

Cross-cultural English teaching is limited by the influence of traditional teaching models, resulting in poor teaching results. In order to improve the efficiency of cross-cultural English teaching, with the support of AI emotion recognition and neural network algorithm, this paper builds a cross-cultural O2O English teaching system with intelligent recognition and management. Moreover, this research uses background models to detect and track targets, to realize the full recognition of students’ emotions, and to facilitate teachers to effectively control online teaching. In addition, combined with online and offline teaching, this study uses neural network algorithm to stabilize the system and perform data processing, construct an overall O2O English teaching model according to actual needs, and formulate the corresponding teaching process. In order to verify the performance of the model, this study starts from two aspects: system performance test and system practice effect and uses statistical methods to collect and process data. The test results show that the model constructed in this paper has good performance and meets expectations.
Image invariant features and SVM techniques for college level English learning platform
Authors: Hu Ping , Diao Lijing
Published: December 2020

Under the Internet information network environment, College English teaching mode is faced with a new choice and transformation. SPOC and STEAM classes have multiple advantages, which can make up for the lack of a single teaching model and provide new ideas for teaching reform. It is a practical application of statistical method to optimize the model of artificial neural network by machine learning method of statistics. The application of mathematical statistics can solve some related problems of artificial perception. Therefore, artificial neural network has the same simple decision ability and judgment ability as human beings. In this paper, the authors analyze the image invariant features and SVM algorithms application in college English education platform. The results show that this method has a positive effect on learners’ English proficiency and learning effect. Teachers also avoid paying a lot of labor, which is very beneficial to the implementation of innovative teaching. However, compared with the traditional teaching, the phenomenon of student achievement differentiation is very serious, and teaching is facing great pressure. Therefore, improving students’ autonomous learning ability and teachers’ information literacy is still very helpful to improve the teaching effect.
Simulation of Chinese online teaching invocational colleges based on complex evolution and improved neural network
Authors: Mei Yang
Published: December 2020

Because the teaching methods of Chinese teaching in higher vocational colleges are improper and the problems in the teaching process cannot be found in time, the teaching effect is not good and there are many difficulties in the teaching process of teachers. According to actual needs, based on complex evolution and improved neural network algorithms, this paper builds a Chinese online teaching system in high vocational colleges. After communication with users and social research, the model function module is determined, and the system performance is improved through the mapping optimization model to eliminate data transmission problems in the system operation, and the realization process of the system function module is shown in the form of a diagram. In addition, this paper designs a control experiment to verify the performance of the model and uses the traditional algorithm model as a control to start the test teaching and uses statistical methods to compare the teaching effects. The research results show that the teaching system constructed in this paper has certain advantages over the traditional model.
Research on economic system based on fuzzy set comprehensive evaluation model
Authors: Wan Min
Published: December 2020

The development of the economic system is affected by many factors, and the stability of the traditional economic analysis model is difficult to maintain. In order to explore the efficient and stable economic system evaluation and analysis model, based on machine learning ideas, this study uses rough set algorithm as the basic algorithm, and applies the related methods of rough set and catastrophe model theory to the evaluation of ecological economic development level. Moreover, this study reduces the redundant index of the index system and calculates the importance of the index after reduction. Based on the catastrophe set model, this study uses MATLAB software programming to comprehensively quantify the ecological economy, and finally divides the ecological economic grade. In addition, this study combines rough set theory with fuzzy mathematics, and initially establishes a two-branch fuzzy evaluation model. Finally, this study combines the actual situation to use the established model to evaluate the regional eco-economic system. The research results show that the method proposed in this paper has a certain effect, which can provide a reference for subsequent related research.
Additive DenseNet: Dense connections based on simple addition operations
Authors: Yu Dawei , Yang Jie , Zhang Yun , Yu Shujuan
Published: December 2020

The Densely Connected Network (DenseNet) has been widely recognized as a highly competitive architecture in Deep Neural Networks. And its most outstanding property is called Dense Connections, which represent each layer’s input by concatenating all the preceding layers’ outputs and thus improve the performance by encouraging feature reuse to the extreme. However, it is Dense Connections that cause the challenge of dimension-enlarging, making DenseNet very resource-intensive and low efficiency. In the light of this, inspired by the Residual Network (ResNet), we propose an improved DenseNet named Additive DenseNet, which features replacing concatenation operations (used in Dense Connections) with addition operations (used in ResNet), and in terms of feature reuse, it upgrades addition operations to accumulating operations (namely ∑ (·)), thus enables each layer’s input to be the summation of all the preceding layers’ outputs. Consequently, Additive DenseNet can not only preserve the dimension of input from enlarging, but also retain the effect of Dense Connections. In this paper, Additive DenseNet is applied to text classification task. The experimental results reveal that compared to DenseNet, our Additive DenseNet can reduce the model complexity by a large margin, such as GPU memory usage and quantity of parameters. And despite its high resource economy, Additive DenseNet can still outperform DenseNet on 6 text classification datasets in terms of accuracy and show competitive performance for model training.