CHLOROPHENOL PHOTODEGRADATION IN WATER BY USE OF TITANIA BASED NANOMATERIALS

Abstract Many of the harmful pollutants such as organic compounds in water are generated diseases in human beings and contaminated our environment. Many industries produce these chemical waste and release into our environment. These chemical compounds created the many problems for the human and environment due the increasing of diseases and contamination of natural water bodies. Therefore, it is not possible to remove 100 percent of these toxic chemicals from the water bodies. We need the green technology which can remove 100 percent of toxic chemicals from the environment. A photocatalyst is defined as "a substance able to produce, by absorption of ultraviolet (UV), visible, or infrared radiation, chemical transformations of the reaction partners, repeatedly coming with them into intermediate chemical interactions and regenerating its chemical composition after each cycle of such interactions. Due to its exceptional qualities like nontoxicity, high photocatalytic degradation ability, and superior thermal and chemical stabilities, TiO2 based photocatalysts demonstrate excellent absorption behavior toward organic molecules in wastewater. Significant environmental contaminants known as chlorophenols have caused major issues for both aquatic and terrestrial life. Therefore, to protect our ecosystem for future generations, their eradication requires urgent, efficient, and cutting-edge solutions. This paper includes a thorough investigation of the uses of chlorophenols, their negative effects, and their photocatalytic breakdown

Comparative Study of Perforated RF MEMS Switch

AbstractMEMS are the Micro Electronic mechanical system or in general terms it is also known as Micro electronic mechanical switch. MEMS have classified in two types of switch that is series switch and shunt switch .The cantilever is a series type switch whereas the fixed- fixed beam is shunt type switch. Fixed- Fixed beam is the element that is fixed at both anchor ends. The electrostatic actuation process occurs on the switch due to which switch deflects from its original position. The stiction problem occurs in MEMS switches which have been reduced by the proposed design. The perforation is used to reduce the squeeze film damping by decreasing the mass of the switch. As the voltage increases the switch moves to downward z-direction .The displacement is produced in the switch as direction of movement is towards negative z-axis. When the beam contacts with electrode, pull in voltage is achieved. This paper explores the perforation and meander concept with Fixed -fixed switch, which increases the flexibility, low actuation voltage and switching speed. The various types of perforations provide discrete displacement corresponding to voltage. In this paper we represent the design and simulation of Fixed-Fixed switch using perforation of size 2μm-5μm. The electrostatic actuation mechanism is applied on the Fixed-fixed switch which has a serpentine meanders and perforation at different voltages. The switch is designed and simulated by using COMSOL®MULTIPHYSICS 4.3b software

Generating probability distributions using variational quantum circuits

We use a variational method for generating probability distributions, specifically, the Uniform, the Normal, the Binomial distribution, and the Poisson distribution. To do the same, we use many different architectures for the two, three and four-qubit cases using the Jensen-Shannon divergence as our objective function. We use gradient descent with momentum as our optimization scheme instead of conventionally used gradient descent. To calculate the gradient, we use the parameter shift rule, whose formulation we modify to take the probability values as outputs instead of the conventionally taken expectation values. We see that this method can approximate probability distributions, and there exists a specific architecture which outperforms other architectures, and this architecture depends on the number of qubits. The four, three and two-qubit cases consist of a parameterized layer followed by an entangling layer; a parameterized layer followed by an entangling layer, which is followed by a parameterized layer and only parameterized layers, respectively

Nearest Neighbor Search over Vectorized Lexico-Syntactic Patterns for Relation Extraction from Financial Documents

Relation extraction (RE) has achieved remarkable progress with the help of pre-trained language models. However, existing RE models are usually incapable of handling two situations: implicit expressions and long-tail relation classes, caused by language complexity and data sparsity. Further, these approaches and models are largely inaccessible to users who don't have direct access to large language models (LLMs) and/or infrastructure for supervised training or fine-tuning. Rule-based systems also struggle with implicit expressions. Apart from this, Real world financial documents such as various 10-X reports (including 10-K, 10-Q, etc.) of publicly traded companies pose another challenge to rule-based systems in terms of longer and complex sentences. In this paper, we introduce a simple approach that consults training relations at test time through a nearest-neighbor search over dense vectors of lexico-syntactic patterns and provides a simple yet effective means to tackle the above issues. We evaluate our approach on REFinD and show that our method achieves state-of-the-art performance. We further show that it can provide a good start for human in the loop setup when a small number of annotations are available and it is also beneficial when domain experts can provide high quality patterns

GPT-FinRE: In-context Learning for Financial Relation Extraction using Large Language Models

Relation extraction (RE) is a crucial task in natural language processing (NLP) that aims to identify and classify relationships between entities mentioned in text. In the financial domain, relation extraction plays a vital role in extracting valuable information from financial documents, such as news articles, earnings reports, and company filings. This paper describes our solution to relation extraction on one such dataset REFinD. The dataset was released along with shared task as a part of the Fourth Workshop on Knowledge Discovery from Unstructured Data in Financial Services, co-located with SIGIR 2023. In this paper, we employed OpenAI models under the framework of in-context learning (ICL). We utilized two retrieval strategies to find top K relevant in-context learning demonstrations / examples from training data for a given test example. The first retrieval mechanism, we employed, is a learning-free dense retriever and the other system is a learning-based retriever. We were able to achieve 3rd rank overall. Our best F1-score is 0.718.Comment: arXiv admin note: text overlap with arXiv:2305.02105 by other author

Analysis of the Performance of IoT Networks in Acoustic Environment by using LZW Data Compression Technique

The Internet of Things (IoT) has experienced phenomenal growth, opening up a wide range of applications in many settings. Due to the properties of sound propagation, IoT networks operating in acoustic environments in particular present special difficulties. Data compression techniques can be used to minimize overhead and maximize resource utilization in these networks to increase performance. The performance of IoT networks in acoustic environments is examined in this study, with a focus on routing overhead, throughput, and typical end-to-end delay. Lempel-Ziv-Welch (LZW) data compression is used to reduce data size and boost communication effectiveness. Three well-known protocols—MQTT, CoAP, and Machine-to-Machine (M2M)—are assessed in relation to acoustic Internet of Things networks. To mimic different acoustic conditions and collect performance metrics, a thorough experimental setup is used. Different network topologies, data speeds, and compression settings are used in the studies to determine how they affect the performance metrics. According to the analysis's findings, all three protocols' routing overhead is greatly decreased by the LZW data compression approach, which enhances network scalability and lowers energy usage. Additionally, the compressed data size has a positive impact on network throughput, allowing for effective data transmission in acoustic contexts with limited resources. Additionally, using LZW compression is seen to minimize the average end-to-end delay, improving real-time communication applications. This study advances knowledge of IoT networks operating in acoustic environments and the effects of data reduction methods on their functionality. The results offer useful information for network engineers and system designers to optimize the performance of IoT networks in similar situations. Additionally, a comparison of the MQTT, CoAP, and M2M protocols' suitability for acoustic IoT deployments is provided, assisting in the choice of protocol for particular application needs

Pseudomonas fluorescens : a potential food spoiler and challenges and advances in its detection

This review focuses on the spoilage strategies used by the Pseudomonas fluorescens, and in addition, it also discusses various diagnostic approaches used for its identification in food items. Some challenges faced and advances in the detection of P. fluorescens and also discussed in this review. An extensive literature search was performed with published work and data was analyzed in detail to meet the requirements of the objectives. P. fluorescens are unicellular rods, with long straight or curved axis, but not helical, motility by one or more polar flagella, Gram-negative, non-spores former, stalks, or sheaths. P. fluorescens is represented by seven biotypes denoted by the letters A, B, C, D, E, F, and G. The microbe shows wide choice of growth temperature and causes contamination and spoilage in ordinary and refrigerated food items by its enzymes and pigment production. The biofilm formation by P. fluorescens poses another serious threat to the food industries. Molecular identification of P. fluorescens is generally done by 16S rRNA, intergenic spacer (ITS1) utilizing traditional polymerase chain reactions (PCR). Nowadays, qPCR and multiplex PCR are largely utilized in identification of P. fluorescens based on AprX gene (extracellular caseinolytic metalloprotease) in the milk and meat spoilage strains. The available methods still show some disadvantages with accuracy and specificity of detection. Rapid detection of P. fluorescens in food samples is the need of hour to improve the detection efficiency

Platelet-rich plasma for the improvement in shoulder function in rotator cuff disorders

Background: Among causes of shoulder pain, rotator cuff disorders are very common. The exact pathogenesis of rotator cuff tears is not clearly understood. To improve outcomes, the relatively new technique of injection of PRP is under investigation. Purpose of this study is to clinically evaluate the efficacy of new treatment of PRP injection in shoulder pain due to rotator cuff pathology.Methods: A prospective, observational study, on patients with shoulder pain diagnosed as rotator cuff disorders admitted in Department of Orthopaedics, RIMS, Ranchi during one year time interval (from 10th October 2016 to 09th October 2017) in the age ranging from 41 to 80 years with a mean age of 57.90 years was conducted. 20 Patients were selected for the study. Initial pre-injection score of patient taken on constant shoulder score and noted. Patient underwent intra-articular injection of PRP in shoulder joint through posterior approach under local anaesthesia. Patients were followed up at 1st post-injection day, 1 month, 3 months and 6 months after the injection.Results: Results were analysed according to constant shoulder score. In partial tear 5 (41.67%) have excellent, 6 (50%) have good and 1 (8.33%) has fair outcome on 6 months follow up and in full tear all 8 (100%) patients have poor outcome and none of the patients developed any complication.Conclusions: A single injection of PRP resulted in a safe, significant, sustained improvement in pain and functional outcomes for patients with refractory partial rotator cuff tear (RCT). 

GMPLS LSP SETUP AND RESTORATION USING ODU PATH LATENCY CRITERIA

The current generation 5G and ultra-high-speed networks have strict requirements of low latency performance from the transmission network. Proposed herein is a mechanism to ensure that a Generalized Multiprotocol Label Switching (GMPLS) Optical Transport Network (OTN)-based transport network considers latency as one of the criteria to establish and reroute OTN Optical Channel Data Unit (ODU) Label Switched Path (LSP) circuits. This will ensure that clients receive the ODU path with latency criteria that satisfy the clients’ specified acceptable limits