Impact of riverbank erosion on riparian society: a micro-level study along the Ganga-Padma river in Samserganj C.D. Block of Murshidabad District, West Bengal

Th e present paper is a micro-level study aimed at analyzing the impacts of riverbank erosion on riparian society. To fulfi ll the objective, the study has been carried out from two distinctive perspectives; viz. general outlooks and specifi c inquiry. For the general outlook, the Ganga-Padma river in its lower reach downstream of Farakka Barrage in Samserganj Community Development Block has been explored in terms of channel shift ing using multi-dated satellite images. For specifi c inquiry, the eff ects of riverbank erosion on society have been studied using primary data in two selected active bank-erosion-prone cadastral units. Th e results show that recurrent bank erosion has brought a drastic change in the social fabric and caused huge losses rendering riparian inhabitants quite vulnerable, since most of the people in the study units are dependent on land-based economy and belong to poor economic groups. Th ese situations necessitate signifi cant outside assistance. However, there is a signifi cant diff erence (χ2 = 10.85 at p<0.01) in terms of assistance received during the previous year between the two selected study units

Stillbirth in a Tertiary Care Referral Hospital in North Bengal - A Review of Causes, Risk Factors and Prevention Strategies

Background and Aims: Stillbirth is one of the most common adverse outcomes of pregnancy, accounting for half of all perinatal mortality. Each year approximately 4 million stillbirths are reported, with 97% occurring in developing countries. The objective of the present study was to evaluate the stillbirth rate, exploring the risk factors and causes of stillbirth and suggest policies to reduce it. Settings and Design: A retrospective study of stillbirth among all deliveries over 5 years at North Bengal Medical College, a referral tertiary care teaching hospital in a rural background. The stillbirth rate and its trend were defined and the probable causes and risk factors were identified. Results: Stillbirth rate is 59.76/1000 live births, and Perinatal Mortality 98.65/1000 births. Of the still births, 59.72% were fresh and 40.27% were macerated. Among the causes of stillbirths, poor antenatal attendance and low socioeconomic status were important; other risk factors included prematurity, PIH, birth asphyxia, poor intrapartum care including prolonged and obstructed labour. In 23% cases, the cause remained unexplained. Conclusion: In addition to poor antenatal care, low socioeconomic condition, poor referral service, suboptimal intrapartum care in health facilities including tertiary centre were mainly responsible for majority of still births which could have been prevented. We speculate that upgrading the existing health system performance, particularly high quality intrapartum care by skilled health personnel, will reduce stillbirths substantially in our institut

IDENTIFICATION OF CAUSES OF DEMAND VARIATION AND ITS IMPACT ON SALES VOLUME - AN EXPLORATORY STUDY IN PROCESSED FOOD INDUSTRY IN BANGLADESH

Demand variation is a key issue in processed food industry, because demands for processed food products vary daily. The organizations in this situation face challenges to meet customer demand. Their products have a definite shelf life and prone to be obsolete. Obsolete products are totally wastes. So, there exists a producer risk. This study has been conducted with the aim of identifying the root causes of demand variation and its impact on sales volume. For this purpose an exploratory study involving two food processing organizations and their forty eight points of sales had been performed. Each food item has different causes and consequences for demand variation. In this regard, three food items having limited shelf life had been selected to find out the causes of their demand variation. The study identified eleven causes and twelve consequences such as special occasion, duration of shelf life, wrong forecasting and so on. Then some root causes are figured out that dominates over others. The impacts of these causes on sales volume are also shown with six months demand data. The research concludes with the level of impact of the significant causes like price, occasion. Lastly some recommendations are mentioned to minimize those root causes of demand variation

Quantum dot polarized light sources

The design, operation and performance of quantum dot spin-polarized vertical cavity surface emitting lasers (VCSELs) and single-photon sources are described and discussed. The effects of spin-induced gain anisotropy on output polarization and threshold current reduction have been studied along with the high-frequency response in a spin-polarized VCSEL. While the output circular polarization in a VCSEL follows the out-of-plane magnetization characteristics of the ferromagnetic spin injector, the output polarization of the spin-polarized single-photon source shows a switching behavior which is explained by invoking the exciton fine structure in the quantum dots and the effects of electron–hole exchange splitting due to in-plane quantum dot rotational asymmetry.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90780/1/0268-1242_26_1_014002.pd

Gate control and amplification of magnetoresistance in a three-terminal device

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98686/1/ApplPhysLett_99_152503.pd

ExpFault: An Automated Framework for Exploitable Fault Characterization in Block Ciphers (Revised Version)

Malicious exploitation of faults for extracting secrets is one of the most practical and potent threats to modern cryptographic primitives. Interestingly, not every possible fault for a cryptosystem is maliciously exploitable, and evaluation of the exploitability of a fault is nontrivial. In order to devise precise defense mechanisms against such rogue faults, a comprehensive knowledge is required about the exploitable part of the fault space of a cryptosystem. Unfortunately, the fault space is diversified and of formidable size even while a single crypto-primitive is considered and traditional manual fault analysis techniques may often fall short to practically cover such a fault space within reasonable time. An automation for analyzing individual fault instances for their exploitability is thus inevitable. Such an automation is supposed to work as the core engine for analyzing the fault spaces of cryptographic primitives. In this paper, we propose an automation for evaluating the exploitability status of fault instances from block ciphers, mainly in the context of Differential Fault Analysis (DFA) attacks. The proposed framework is generic and scalable, which are perhaps the two most important features for covering diversified fault spaces of formidable size originating from different ciphers. As a proof-of-concept, we reconstruct some known attack examples on AES and PRESENT using the framework and finally analyze a recently proposed cipher GIFT [BPP + 17] for the first time. It is found that the secret key of GIFT can be determined with 2 nibble fault instances injected consecutively at the beginning of the 25th and 23rd round with remaining key space complexity of 2^7.06

Differential Fault Analysis Automation

Characterization of all possible faults in a cryptosystem exploitable for fault attacks is a problem which is of both theoretical and practical interest for the cryptographic community. The complete knowledge of exploitable fault space is desirable while designing optimal countermeasures for any given crypto-implementation. In this paper, we address the exploitable fault characterization problem in the context of Differential Fault Analysis (DFA) attacks on block ciphers. The formidable size of the fault spaces demands an automated albeit fast mechanism for verifying each individual fault instance and neither the traditional, cipher-specific, manual DFA techniques nor the generic and au- tomated Algebraic Fault Attacks (AFA) [10] fulfill these criteria. Further, the diversified structures of different block ciphers suggest that such an automation should be equally applicable to any block cipher. This work presents an automated framework for DFA identification, fulfilling all aforemen- tioned criteria, which, instead of performing the attack just estimates the attack complexity for each individual fault instance. A generic and extendable data-mining assisted dynamic analysis frame- work capable of capturing a large class of DFA distinguishers is devised, along with a graph-based complexity analysis scheme. The framework significantly outperforms another recently proposed one [6], in terms of attack class coverage and automation effort. Experimental evaluation on AES and PRESENT establishes the effectiveness of the proposed framework in detecting most of the known DFAs, which eventually enables the characterization of the exploitable fault space

Leakage Assessment in Fault Attacks: A Deep Learning Perspective

Generic vulnerability assessment of cipher implementations against fault attacks (FA) is a largely unexplored research area to date. Security assessment against FA is particularly important in the context of FA countermeasures because, on several occasions, countermeasures fail to fulfil their sole purpose of preventing FA due to flawed design or implementation. In this paper, we propose a generic, simulation-based, statistical yes/no experiment for evaluating fault-assisted information leakage based on the principle of non-interference. The proposed exper- iment is oblivious to the structure of countermeasure/cipher under test and detects fault-induced leakage solely by observing the ciphertext dis- tributions. Unlike a recently proposed approach that utilizes t-test and its higher-order variants for detecting leakage at different moments of ciphertext distributions, in this work, we present a Deep Learning (DL) based leakage detection test. Our DL-based detection test is not specific to only moment-based leakages and thus can expose leakages in several cases where t-test based technique demands a prohibitively large number of ciphertexts. We also present a systematic approach to interpret the leakages from DL models. Apart from improving the leak- age detection test, we explore two generalizations of the leakage assess- ment experiment itself – one for evaluating against the Statistical ineffec- tive fault model (SIFA), and another for assessing fault-induced leakages originating from “non-cryptographic” peripheral components of a secu- rity module. Finally, we present techniques for efficiently covering the fault space of a block cipher by exploiting logic-level and cipher-level fault equivalences. The efficacy of DL-based leakage detection, as well as the proposed generalizations, has been evaluated on a rich test-suite of hardened implementations from several countermeasure classes, includ- ing open-source SIFA countermeasures and a hardware security module called Secured-Hardware-Extension (SHE)

Evaluation of Antihyperglycemic Activity of Citrus limetta Fruit Peel in Streptozotocin-Induced Diabetic Rats

The present paper aims to evaluate antihyperglycemic activity of methanol extract of Citrus limetta fruit peel (MECL) in streptozotocin-induced (STZ; 65 mg/kg b.w.) diabetic rats. Three days after STZ induction, diabetic rats received MECL orally at 200 and 400 mg kg−1 body weight daily for 15 days. Glibenclamide (0.5 mg kg−1 p. o.) was used as reference drug. Blood glucose levels were measured on 0th, 4th, 8th, and 15th days of study. Serum biochemical parameters namely, SGOT, SGPT and ALP were estimated. The TBARS and GSH levels of pancreas, kidney, and liver were determined. MECL significantly (P < 0.001) and dose dependently normalized blood glucose levels and serum biochemical parameters, decreased lipid peroxidation, and recovered GSH as compared to those of STZ control. The present paper infers that in STZ-induced diabetic Wistar rats, C. limetta fruit peel demonstrated a potential antihyperglycemic effect which may be attributed to its antioxidant property