Use of spent sulphite liquor for stabilization of fractured rock and sealing off water bearing formations

The paper industry, in its process of manufacturing pulp from wood, produces large quantities of a substance called lignin, lignin sulphite, or lignosulphonate. This material has been disposed of as a waste product; however, it does have many potential uses. In this investigation, lignosulfonates were used as agents for bonding rock sections together and, as the chief component of gels, for filling the pores of artificial rock cores. The purposes of these tests were to find how this substance could be used in the mining industry, for stabilizing fractured ground around mine openings and for sealing off water influx into mine openings. Strength tests conducted on cemented sections of rock and permeability tests conducted on the sealed cores indicated that lignosulfonates would make effective stabilizing and sealing compounds, when used under the proper physical conditions and when the correct proportions of chemicals were employed. a major advantage of this substance over other cementing or sealing agents is its los cost, which in most cases would be far less than any other known substances used for these purposes --Abstract, page ii

Maxillary Hollow Denture: A Case Series

Retention, stability and support are the basic principles on which the success of a complete denture relies on. The skill lies in applying these principles efficiently in critical situations. Residual ridge resorption occurs at a three times faster rate in mandibular arch than in the maxillary arch. The severely resorbed maxillary and mandibular edentulous arches that are narrow and constricted with increased interarch space provide decreased support, retention and stability. The consequent weight of the processed complete denture only compromises them further. The severely resorbed jaw can have various treatment option. This clinical report describes three case reports of an edentulous patients with resorbed ridges where a simplified technique of fabricating a light weight hollow maxillary complete denture was used for the preservation of denture bearing areas

Brian Moore: An Ambassador of Feminism

The present research paper explores the significance of Brian Moore as an angel of feminism through the study of his portrayal of female characters with special context of Irish novels in the 20th century Ireland. He is grown up in a Catholic family. He is one of his parent’s nine children. This paper studies his depiction of women characters with special context to the novels The Feast of Lupercal and Lies of Silence. He has raised the true voice of women of contemporary society at Belfast in Ireland through his fiction. The Feast of Lupercalis the story of a Catholic school teacher, Diarmuid Devine and his girlfriend a Protestant girl, Una Clarke. She is the main female character in this novel. She has been exploited mentally and physically by her ex-boyfriend Michael who was a married man. Later she meets Diarmuid Devine who plays with her emotions and leaves her due to Catholic restrictions. Moore in his next novel Lies of Silence (1990) presents the struggle among the Catholicism, the Protestantism and political uncertainty in Belfast. The main characters in this novel are Michael Dillon and his wife Moira Dillon. Moira Dillon is an innocent, beautiful and well educated unemployed woman. Her husband deceives her and wants to divorce her. She accepts the reality of life and emerges as liberal, bold and patriotic. This paper brings out Brian Moore’s true ability to reveal the world of women through his Irish fiction

Effectiveness of modified mattress suture closing technique over conventional lower segment caesarean section closing technique

Background: The objective of this study was to compare the thickness of the scar and relative thinning of the uterinewall following conventional LSCS closing technique versus new closing technique (modified mattress Suture) and any additional surgical procedure in each group.Methods: A total of sixty patients undergoing primary caesarean for obstetric indications and who were willing for the study were included. In 30 patients uterus was closed by conventional double layer technique (the first layer is suturing with absorbable suture in a continuous running fashion. After first layer is complete, a second continuous stitch is used to invert the first layer, inverting stitch may be horizontal or vertical using same suturing material) and in 30 patient uterus was closed by new modified mattress technique. In both groups same suture material (vicryl 1-0) was used. Measurement of the thickness of scar site and corresponding posterior wall thickness was done following 6 months of caesarean section.Results: The possible parameters of better technique i.e., the mean scar thickness is more and relative as well as percentage thinning is less with this new technique of uterine closure although statistically not significant. Conclusions: Modified mattress suture technique is a single step procedure and gives the feel of double layer uterine closure. Hence the time taken, material. Used and the cost involved will be less along with excellent hemostasis

A Comparative Study of Learning Styles of Students on the basis of their economic condition

Every student has their own unique learning style. Knowledge of one’s learning styles can be used to increase self-awareness about their strengths and weaknesses as student. Sometimes the learning styles may affected by some external factors like economic condition. This research is a comparative study of learning styles of students on the basis of their economic condition. In this research paper as sample we have taken 10 students which are BPL (Below Poverty Line)  and 10 students which are APL (Above Poverty Line) of the age group 14-21 years of four cities from Nainital District (Haldwani, Ramnagar, Nainital, and Kaladhungi). We used Learning Style Inventory (by- K. S. Mishra) to collect data. In the study, the result rejects our hypothesis that there will be a significant impact of economic condition of students on the learning of students

GlyphNet: Homoglyph domains dataset and detection using attention-based Convolutional Neural Networks

Cyber attacks deceive machines into believing something that does not exist in the first place. However, there are some to which even humans fall prey. One such famous attack that attackers have used over the years to exploit the vulnerability of vision is known to be a Homoglyph attack. It employs a primary yet effective mechanism to create illegitimate domains that are hard to differentiate from legit ones. Moreover, as the difference is pretty indistinguishable for a user to notice, they cannot stop themselves from clicking on these homoglyph domain names. In many cases, that results in either information theft or malware attack on their systems. Existing approaches use simple, string-based comparison techniques applied in primary language-based tasks. Although they are impactful to some extent, they usually fail because they are not robust to different types of homoglyphs and are computationally not feasible because of their time requirement proportional to the string length. Similarly, neural network-based approaches are employed to determine real domain strings from fake ones. Nevertheless, the problem with both methods is that they require paired sequences of real and fake domain strings to work with, which is often not the case in the real world, as the attacker only sends the illegitimate or homoglyph domain to the vulnerable user. Therefore, existing approaches are not suitable for practical scenarios in the real world. In our work, we created GlyphNet, an image dataset that contains 4M domains, both real and homoglyphs. Additionally, we introduce a baseline method for a homoglyph attack detection system using an attention-based convolutional Neural Network. We show that our model can reach state-of-the-art accuracy in detecting homoglyph attacks with a 0.93 AUC on our dataset

Online Learning Management System and Analytics using Deep Learning

During this pandemic we have seen rise in popularity of online learning platforms. In this paper, we are going to discuss E-Learning using analytics and deep learning focusing on mainly four objectives which are login systems for teachers and students, Gamification to engage learners, AR contents to increase the involvement of learners and learning analytics to develop competency. We will use Data Mining and Buisness Intelligence to extract high level knowledge from the raw data of students. To predict engagement of students we have used several ML algorithms. This study provides an introduction to the technology of AR and E-Learning systems. The main focus of this paper is to use research on augmented reality and integrate it with Buisness Intelligence and Data Mining(DM). Engaging student till the end of the course became really difficult for traditional E-Learning Platform. Therefore, Gamification in E-learning is good way to solve this problem

A short antisense oligonucleotide masking a unique intronic motif prevents skipping of a critical exon in spinal muscular atrophy

Spinal muscular atrophy (SMA) is the leading genetic cause of infant mortality. Most SMA cases are associated with the low levels of SMN owing to deletion of Survival Motor Neuron 1 (SMN1). SMN2, a nearly identical copy of SMN1, fails to compensate for the loss of SMN1 due to predominant skipping of exon 7. Hence, correction of aberrant splicing of SMN2 exon 7 holds the potential for cure of SMA. Here we report an 8-mer antisense oligonucleotide (ASO) to have a profound stimulatory response on correction of aberrant splicing of SMN2 exon 7 by binding to a unique GC-rich sequence located within intron 7 of SMN2. We confirm that the splicing-switching ability of this short ASO comes with a high degree of specificity and reduced off-target effect compared to larger ASOs targeting the same sequence. We further demonstrate that a single low nanomolar dose of this 8-mer ASO substantially increases the levels of SMN and a host of factors including Gemin 2, Gemin 8, ZPR1, hnRNP Q and Tra2-β1 known to be down regulated in SMA. Our findings underscore the advantages and unmatched potential of very short ASOs in splicing modulation in vivo

Hierarchical Deep Learning Architecture For 10K Objects Classification

Evolution of visual object recognition architectures based on Convolutional Neural Networks & Convolutional Deep Belief Networks paradigms has revolutionized artificial Vision Science. These architectures extract & learn the real world hierarchical visual features utilizing supervised & unsupervised learning approaches respectively. Both the approaches yet cannot scale up realistically to provide recognition for a very large number of objects as high as 10K. We propose a two level hierarchical deep learning architecture inspired by divide & conquer principle that decomposes the large scale recognition architecture into root & leaf level model architectures. Each of the root & leaf level models is trained exclusively to provide superior results than possible by any 1-level deep learning architecture prevalent today. The proposed architecture classifies objects in two steps. In the first step the root level model classifies the object in a high level category. In the second step, the leaf level recognition model for the recognized high level category is selected among all the leaf models. This leaf level model is presented with the same input object image which classifies it in a specific category. Also we propose a blend of leaf level models trained with either supervised or unsupervised learning approaches. Unsupervised learning is suitable whenever labelled data is scarce for the specific leaf level models. Currently the training of leaf level models is in progress; where we have trained 25 out of the total 47 leaf level models as of now. We have trained the leaf models with the best case top-5 error rate of 3.2% on the validation data set for the particular leaf models. Also we demonstrate that the validation error of the leaf level models saturates towards the above mentioned accuracy as the number of epochs are increased to more than sixty.Comment: As appeared in proceedings for CS & IT 2015 - Second International Conference on Computer Science & Engineering (CSEN 2015

Preparation and Characterization of Nanostructured CaCu2.90 Zn0.10 Ti4O12 Ceramic

Nanostructure CaCu2.90Zn0.10Ti4O12 (CCZTO) electronic ceramic was synthesized by semi‐wet route. The objective of this route is to enable the calcination and sintering processes to go for completion in shorter time and at lower temperature.The samples were characterized by XRD, TEM, SEM and EDX analyses. The crystallite size of the CCZTO ceramic, obtained by XRD using Debye Scherrer formula, range from 38‐74nm which is in good agreement with the particle size observed by TEM analysis. It was observed clearly that the grain size significantly increased with an increase in sintering duration. Dielectric measurements were carried out by LCR meter in the temperature range, 300‐  500K, at few selected frequencies. It was also observed that the dielectric constant and dielectric loss of CCZTO are temperature independent in higher frequency whereas temperature dependent in low frequency region. The ceramics exhibit high dielectric constant of 1.35 x 10 4 at 1 kHz