Objective: To assess breastfeeding knowledge, attitudes, and practices (KAP) among Indian suburban mothers and evaluate their correlation with infant anthropometric outcomes, identifying socioeconomic and behavioral factors associated with growth faltering. Methods: Cross-sectional study of 60 mother-infant dyads in Zahreeabad, Telangana. Data included structured questionnaires on demographics and KAP metrics, plus objective anthropometric measurements compared against age-/sex-matched standards. Descriptive and correlational analyses examined associations between maternal factors and infant growth. Results: Mean maternal age was 27.47±4.24 years; 75% were homemakers(N=45), 60% held Bachelor's degrees or higher (N=36). Early breastfeeding initiation (≤1 hour) occurred in 65%(N=39), with universally positive attitudes. Maternal education is significantly correlated with breastfeeding knowledge (p=0.824), though knowledge scores didn't differ between mothers maintaining versus discontinuing exclusive breastfeeding (EBF). Descriptively, c-section infants showed 2.42 cm greater length deficits than vaginal births. Despite 85% of infants exhibiting stunting and 55% showing weight deficits, 85% of mothers rated growth as "Average" or "Above Average," revealing a critical perception-reality gap. Conclusions: High breastfeeding knowledge and positive attitudes don't prevent growth faltering, with 85% of infants stunted despite strong maternal awareness. Structural barriers—particularly C-sections (85% of delayed initiations) and early complementary feeding (p = .042)—critically impair outcomes. A profound perception gap exists: 85% of mothers rated stunted growth as "Average" or above. Interventions must address clinical barriers and maternal perceptual frameworks, not just knowledge dissemination.

Recently, linear codes constructed from defining sets have been studied extensively. For an odd prime p, let Trm e be the trace function from Fpm onto Fpe, where e is a divisor of m. In this paper, for the defining set D = {x ∈ F∗ pm : Trm e (x2 + x) = 0} = {d1,d2,...,dn} (say), we define a pe-ary linear code CD by CD ={cx =Trm e (xd1),Trm e (xd2),...,Trm e (xdn) : x ∈ Fpm} and present three-weight and five-weight linear codes with their weight distributions. We show that each nonzero codeword of CD is minimal for m e ≥ 5 and, thus, such codes are applicable in secret sharing schemes.

Recently, the concept of smart cities has gained a IoT of popularity. Because of the growth of the Internet of Things(IoT), the idea of a smart city today seems feasible. Ongoing research on the Internet of Things is being done to improve the effectiveness and dependability of urban infrastructure. Road safety issues, parking shortages, and traffic congestion are among the issues that the Internet of Things is being used to address. In this work, author present a cloud- integrated Internet of Things-based smart parking system. The placement of an IoT on the property is required for the proposed smart parking system in order to track the availability of each specific parking space. Additionally, a smartphone app is provided to assist customers in determining parking availability.

In this paper, a novel two-dimensional (2D) finite impulse response (FIR) filter is proposed using Vedic multiplier architecture. Several multipliers, like Vedic, array, Booth, and Wallace tree, are employed in the construction of filters to reduce filter area and power consumption. The VM lowers the partial products (PP) in multiplication among various multipliers. As a result, multiplication happens more quickly. The VM uses a sutra known as “Urdhva Tiryakbhyam,” which is based on ancient mathematics. Two techniques to maximize speed, area, and power are suggested in this research. The first technique makes use of a VM predictor block and the second method is based on reusable block for the VM. The proposed novelty design is coded by Verilog HDL and synthesized using Xilinx 14.7 tool. The proposed design results are compared with existing designs. The number of slices required for 2D FIR using VM is less when compared with FIR with normal multiplier.

This research study intends to develop an interface for product recommendation system using collaborative filtering. Product recommendation system used for recommending to the users about the products based on their previous purchases and search results. The final product is a fully functional interface that demonstrates the potential of collaborative filtering and its application in building the product recommendation system.

The Internet of Things (IoT) is the 21st century’s fastest-growing technology. Nearly by the end of 2025, 75 billion IoT devices will be get connected to the internet. As a result, safeguarding devices from attacks and maintaining user privacy-related data has become extremely difficult. In this paper, we propose an efficient model to detect security and privacy related threats in IoT environment using different machine learning and deep learning algorithms on open-source standard dataset like NSL-KDD (Knowledge Discovery Data) and UNSW-NB15, which were made accessible for conducting research activities purposes. Here we analyzed the feature set of the data required to detect various threats mentioned in the given dataset using proposed model. This paper examines the binary and multiclass attacks classification using neural network and machine learning approaches. RNN model outperformed with higher accuracy in detecting threats with 99.4 percent for binary classification and 96.2 percent for multiclass classification.

Cloud Service Selection is still one of the critical decisions that have the highest impact on any association.Making a decision scrutinizing them with estimation is always a complicated task.This paper implemented a three-step process in service selection: Cloud Service Scrutinization, Assessment, and Selection Framework (CSESF) using K Nearest Neighbor -cosine metrics.In this method, all the decision-maker's requirements are initially identified and listed.All the parameters and service providers are listed.An algorithm for scrutinizing is developed.Weights are calculated for preferences given by the decisionmakers.KNN with cosine metrics works on choosing the service with the smallest for the positive best solution and harmful for the far solution.The results show that CSESF is robust, practical, and suitable for choosing the service.

For an odd prime p and a positive integer m, let 𝔽_p^m be the finite field with p^m elements. For D_1={d∈𝔽_p^m^* : Tr_e^m(d^2)=0}={d_1,d_2,… ,d_n} (say) and D_2={d∈𝔽_p^m : d^k=1} ( k=p^l-1 for a divisor l of m), first we define classical linear codes by 𝒞_D_1= {(Tr_e^m(ad_1), Tr_e^m(ad_2),… ,Tr_e^m(ad_n)): a∈𝔽_p^m}; 𝒞_D_1= {( u+Tr_e^m(ad_1),u+Tr_e^m(ad_2),… ,u+Tr_e^m(ad_n)): a∈𝔽_p^m, u∈𝔽_p^e}; 𝒞_D_2= {(Tr_e^m(ad_1),… ,Tr_e^m(ad_k), u+Tr_e^m(ad_1),… ,u+Tr_e^m(ad_k)): a∈𝔽_p^m, u∈𝔽_p^e}, where Tr^m_e denotes the trace function from 𝔽_p^m onto 𝔽_p^e and e is a divisor of m. Then we determine weight distribution of the code 𝒞_D_1∖𝒞_D_1 and construct quantum codes from the codes 𝒞_D_1 and 𝒞_D_1 based on CSS code construction. Finally, we construct quantum code from the code 𝒞_D_2 and show that the code obtained from 𝒞_D_2 is MDS if and only if s=1, where s=m/e .

The study aims to find out the publication details of Prof. C N R Rao which has been indexed under the Web of Science database over the period of 20 Years from 2001 to 2020. The methodology adopted for the present research study is scientometrics tools such as authorship pattern and collaboration, degree of collaboration, and citations. The study has revealed that a total of 371 publications contributed by Prof. CNR Rao in collaboration up to the end of the year 2009, no one publications are indexed in the web of science contributed by CNR after 2009. The highest 305 publications are articles were published in journals and a maximum of 125 publications was in three authorship patterns. He has contributed most of his (72.24%) publications in the field of chemistry. The mean value of the Degree of Collaboration is 0.97.

Nucleophosmin (NPM1) mutation is one of the most common recurring genetic abnormalities seen in acute myeloid leukemia (AML). Immunohistochemistry serves as a cost effective and simple surrogate testing method for detection of NPM1 mutation. This study was conducted to evaluate the frequency of aberrant cytoplasmic nucleophosmin 1 expression in leukemic blast cells on formalin fixed bone marrow trephine biopsy (BMB) sections and also to correlate this data with the reference molecular method (reverse transcriptase-polymerase chain reaction; RT-PCR and gene sequencing), where available. Immunostains were performed using mouse anti-NPM1 monoclonal antibody on 71 paraffin embedded bone marrow biopsies (BMB) of patients with AML of any French-American-British (FAB) subtype. Results of immunohistochemistry (IHC) were then compared with the reference molecular method. The proportion of NPM1 expression by immunostaining in AML cases was found to be 17%. Twelve of the total 71 cases demonstrated cytoplasmic nucleophosmin (NPMc+) on immunostaining. Eleven of the positive cases that were correlated with the molecular standard demonstrated mutation in exon 12 of NPM1 gene. Cytoplasmic nucleophosmin expression by immunostaining was found to be in complete agreement with the standard molecular method. In a resource restricted setup, the information from this study might help in providing an inexpensive and accurate detection method to facilitate introduction of this marker in diagnostic and prognostic workup of AML especially in patients showing normal karyotype and no common recurrent translocations.

There are many different types of fauna and flora in the earth. Vegetation is regarded as the most significant source of life for all living things. When it comes to vegetation, the leaf is considered as the most important component. The leaves must be preserved for agricultural purposes. It's also critical to identify the type of leaf and preserve it so that it may be utilised again in the future. It is quite easy to know the type of leaf without even knowing about vegetation if it is automated. In this paper, an automated Hybrid approach of SVM+BDT (Support Vector Machine with Binary Decision Tree) Leaf classification system is proposed. From the results, it is evident that, the proposed hybrid approach classifies the leaf with 92% accuracy.

The research paper detail with the very important issue that how to provide Security to home which is under threat from the thief for burglary sometime person life will be in danger and now a day, the thief have become more advance in doing burglary not only home but bank shopping mall and gold & diamond jewellery and so to protect not only this building but also our houses, this research paper discuss about protection of building by using PIR sensor wich is a motion detector along with nodeMCU and mobile phone application which is called as Blynk we have to installed this application in our mobile phones this application will be active in phone and a screen will when a motion is detected by pir sensor

For any positive integer m > 2 and an odd prime p, let $\mathbb {F}_{p^{m}}$ be the finite field with pm elements and let $ \text {Tr}^{m}_{e}$ be the trace function from $\mathbb {F}_{p^{m}}$ onto $\mathbb {F}_{p^{e}}$ for a divisor e of m. In this paper, for the defining set $D=\{x\in \mathbb {F}_{p^{m}}:\text {Tr}^{m}_{e}(x)=1\text { and } \text {Tr}^{m}_{e}(x^{2})=0\}=\{d_{1}, d_{2}, \ldots , d_{n}\}$ (say), we define a pe-ary linear code $\mathcal {C}_{D}$ by $$ \mathcal{C}_{D}=\{\textbf{c}_{a} =\left( \text{Tr}^{m}_{e}(ad_{1}), \text{Tr}^{m}_{e}(ad_{2}),\ldots,\text{Tr}^{m}_{e}(ad_{n})\right) : a\in \mathbb{F}_{p^{m}}\}. $$ Then we determine the complete weight enumerator and weight distribution of the linear code $\mathcal {C}_{D}$ . The presented code is optimal with respect to the Griesmer bound provided that $\frac {m}{e}=3$ . In fact, it is MDS when $\frac {m}{e}=3$ . This paper gives the results of S. Yang, X. Kong and C. Tang (Finite Fields Appl. 48 (2017)) if we take e = 1. In addition to the generalization of the results of Yang et al., we study the dual code $\mathcal {C}_{D}^{\perp }$ of the code $\mathcal {C}_{D}$ as well as find some optimal constant composition codes.

Crop production plays a significant role in the agricultural sector. The loss of food is primarily attributed to contaminated crops, which reflexively decreases the rate of development. The detection of plant disease within the field of agriculture is extremely difficult. When identification is incorrect then the assembly of the product and the market's economic value will suffer a significant loss. This research involves a new approach to model identification of plant diseases growth using large, convolution networks, based on the classification of the leaf image. Novel approach and technique used to promote the easy and simple implementation of the program in observance. The developed model can identify thirteen completely different kinds of plant diseases from healthy leaves, with the flexibility to tell apart from the surrounding plant leaves. This technique for the identification of diseases was projected for the first time according to our knowledge. All necessary steps were taken by agricultural consultants to incorporate this disease recognition model, beginning with the collection of photographs to make details. Python & PyCham are used to do the deep CNN process.

Introduction:The use of ionizing radiation in medical imaging for diagnostic and interventional purposes has risen dramatically in recent years with a concomitant increase in exposure of patients and health workers to radiation hazards.Objective: To study the knowledge on radiation hazards and radiation protection among MBBS students in Dakshina Kannada district. Methods:A cross-sectional study was conducted among 134 medical students.The study comprised of administration of standardized semi-structured pre-tested questionnaire to obtain information on socio-demographic characteristics, knowledge of radiation hazards and radiation protection.Knowledge was scored, +1 was given for the correct answer and 0 for the incorrect answer.Scoring was done.Statistical analysis was performed using Microsoft Excel 2016 software and descriptive statistics were expressed. Results:The participants were aged between 18 to 22 years above, most of them were females.93.27% of subjects had good knowledge of radiation hazards.78 % of subjects had good knowledge of radiation personal protective devices.6 % of subjects had poor knowledge of both radiation hazards and radiation protection. Conclusion:In conclusion, the students in the present study had good knowledge of radiation hazards but show relatively poorer knowledge of radiation protection.We are recommended that the curriculum of medical college be expanded further to provide better exposure to radiation protection and its practice so that these students on graduation will be well-grounded with the best principle of radiation protection.This in turn helps in the protection of the patients, operator and public from the harmful effects of radiation.

Background: OSMF is one of the disorders affecting oral cavity, and sometimes pharynx. It is kind of potential malignant disorder associated with betel nut chewing and some nutritional deficiencies. Medical treatment of OSMF has been not completely systematized and no perfect and broadly accepted treatment is presently accessible for this condition. Objective: To evaluate the efficacy of PRP and hyluronidase injections for the management of OSMF. Materials and Methods: Present study was carried out in 30 patients with OSMF of different clinical grade (Grade III, IV, V). The patients were administered with 0.5 ml of Hyaluronidase 1,500 IU was mixed in 1 ml of lignocaine as well as 0.5 ml of PRP (Platelets rich plasma) injected intralesionally in fibrosis of OSMF, once a week. Results: Results of ANOVA suggested that after treatment with these two injections there were significant improvement or relief in symptoms were observed. Thus treatments significantly work to relief the symptoms. There was significant difference found between pre and post treatment (p value\u003c0.05). Conclusion: Treatment with hyaluronidase and PRP is an efficient mean of managing OSMF and can decrease the symptoms and provide relief to the certain extent.

Background: India generates about 60 million tonnes of garbage every day, of this around 45 to 50 million tonnes is left untreated. Wastes are thrown on the streets. Open defecation is still a problem in rural India. All these actions cause health hazards among population. Objective: To assess the knowledge, attitude and practices regarding Swachh Bharat among 8th to 10th standard students. Methodology: This cross-sectional study was carried out in seven government high schools in the field practice area of a medical college in Mangalore. A total of 441 government high school students from 8th to 10th standard were included in the study. Collection of data was done by interview method using pretested semi structured questionnaire. Results: Total of 441 students were included in the study. 55.32% were boys and 44.68% were girls. According to scoring done for students, 84.35% had good knowledge, 95.23% had good attitude but only 50.34% had good practice about environmental cleanliness and personal hygiene. Conclusion: To improve the good practice various health educations and practical demonstrations about the cleanliness and benefits of practicing them can be conducted as school-based initiatives to create awareness among students.