Implementing the Great American Outdoors Act in the Era of Sustainable Recreation: Time for a Mission 2030?

The Great American Outdoors Act (AGOA) fully and permanently funds the Land and Water Conservation Fund for the first time since it was created in 1964. This is a boon for purchasing conservation lands, but equally important, the act provides funding to address massive federal agency recreation infrastructure backlogs. The last major overhaul of the U.S. parks and outdoor recreation system was over 50 years ago, during the era of Mission 66 and related programs. Since that time, a host of environmental and societal changes necessitates new approaches for updating conservation and recreation opportunities. In addition to acquiring critical park and conservation lands, and developing and updating facilities, new park and recreation goals include increasing public use and visitor diversity and advancing environmental justice, public health, and large-scale conservation goals. Integrated systems analyses are needed to address these diverse concerns across landscapes, regions, and jurisdictions, and new interagency and interdisciplinary approaches will be needed. This is a bureaucratic crossroads: for the first time in decades we can truly advance public access, human health, and social equity values of public lands; the GAOA is a critical process step toward, but not the culmination of, this goal.

WAVELET DETAIL COEFFICIENT AS A NOVEL WAVELET-MFCC FEATURES IN TEXT-DEPENDENT SPEAKER RECOGNITION SYSTEM

Speaker recognition is the process of recognizing a speaker from his speech. This can be used in many aspects of life, such as taking access remotely to a personal device, securing access to voice control, and doing a forensic investigation. In speaker recognition, extracting features from the speech is the most critical process. The features are used to represent the speech as unique features to distinguish speech samples from one another. In this research, we proposed the use of a combination of Wavelet and Mel Frequency Cepstral Coefficient (MFCC), Wavelet-MFCC, as feature extraction methods, and Hidden Markov Model (HMM) as classification. The speech signal is first extracted using Wavelet into one level of decomposition, then only the sub-band detail coefficient is used as the feature for further extraction using MFCC. The modeled system was applied in 300 speech datasets of 30 speakers uttering “HADIR” in the Indonesian language. K-fold cross-validation is implemented with five folds. As much as 80% of the data were trained for each fold, while the rest was used as testing data. Based on the testing, the system's accuracy using the combination of Wavelet-MFCC obtained is 96.67%. ABSTRAK: Pengecaman penutur adalah proses mengenali penutur dari ucapannya yang dapat digunakan dalam banyak aspek kehidupan, seperti mengambil akses dari jauh ke peranti peribadi, mendapat kawalan ke atas akses suara, dan melakukan penyelidikan forensik. Ciri-ciri khas dari ucapan merupakan proses paling kritikal dalam pengecaman penutur. Ciri-ciri ini digunakan bagi mengenali ciri unik yang terdapat pada sesebuah ucapan dalam membezakan satu sama lain. Penyelidikan ini mencadangkan penggunaan kombinasi Wavelet dan Mel Frekuensi Pekali Cepstral (MFCC), Wavelet-MFCC, sebagai kaedah ekstrak ciri-ciri penutur, dan Model Markov Tersembunyi (HMM) sebagai pengelasan. Isyarat penuturan pada awalnya diekstrak menggunakan Wavelet menjadi satu tahap penguraian, kemudian hanya pekali perincian sub-jalur digunakan bagi pengekstrakan ciri-ciri berikutnya menggunakan MFCC. Model ini diterapkan kepada 300 kumpulan data ucapan daripada 30 penutur yang mengucapkan kata "HADIR" dalam bahasa Indonesia. Pengesahan silang K-lipat dilaksanakan dengan 5 lipatan. Sebanyak 80% data telah dilatih bagi setiap lipatan, sementara selebihnya digunakan sebagai data ujian. Berdasarkan ujian ini, ketepatan sistem yang menggunakan kombinasi Wavelet-MFCC memperolehi 96.67%.

Optimized Cell Mixing Facilitates the Reproducible Bioprinting of Constructs with High Cell Viability

Bioprinting with cell-laden hydrogels (bioink) requires the careful mixing of cells with the hydrogel carrier to ensure that the bioink is homogeneous and functional, and the printing results are reproducible. Bioink preparation is therefore a critical process step that must accommodate the specific rheological properties of different bioinks. Here, we developed a reproducible method for the optimized mixing of cells and hydrogel carriers that can be integrated into current bioprinting processes. First, we tested and optimized different mixing devices for their effect on bioink homogeneity and rheological properties, resulting in a low-shear process for the preparation of homogenous bioinks. Based on these findings, we evaluated the impact of different cell densities on the rheological profile of bioinks according to shear and temperature, and estimated the impact of shear stress intensity and duration on 1.1B4 cells. Finally, we integrated the optimized mixing method into a current printing process and monitored the printed construct for 14 days to confirm cell viability. We found that the cell viability in the printed cell-laden constructs remained in excess of 91% after 14 days.

A Review on Various Analytical Methodologies for Etoricoxib

Etoricoxib belongs to the class of highly selective COX-2 inhibitor NSAIDs. It is mostly used for the treatment of pain, arthritic conditions including rheumatoid arthritis and osteoarthritis. The current study focuses primarily on analytical and bioanalytical method development methodologies, as well as numerous methods established for the estimation of etoricoxib, whether in pharmaceutical dose form or in bulk. Analytical procedures are critical for determining compositions, as they allow us to obtain both qualitative and quantitative results utilising advanced analytical tools. The analytical method for Etoricoxib may be chromatographic, electrochemical, spectral or hyphenated. These methods aid in the comprehension of critical process parameters as well as the minimization of their impact on precision and accuracy. Analytical method development is required to sustain high commercial product quality standards and to meet regulatory requirements. Following the reference, regulatory organisations in several nations have established standards and procedures for providing approval, authentication, and registration. Bioanalytical methods are designed to quantify the concentration of drug, metabolite, or typical biomarkers from various biological fluids including serum, urine, saliva and tissue extracts.

Decision Tree-based Hybrid Multiprocessor Task Scheduling for the Cyber-Physical System

Scheduling is a critical process in cyber-physical systems to ensure the computation will be over within the physical system's deadline. Under the cyber-physical system, the processor is distributive and hydrogenous. Less latency task scheduling under this distributive cyberphysical system with a hydrogenous processor and resource is challenging. This article presents a decision tree based less complex mechanism of task scheduling in a heterogeneous processor environment this proposed mechanism model the tasks and the processor resource, current load level, their individual computational capability, memory availability, communication delay in the distributive system to move the task from one point to another point is taken into account for the scheduling purpose the numerical results prove that the proposed mechanism able to schedule the task quickly and with more task deadline meet the ratio.

A Data-Driven Framework to Predict Fused Filament Fabrication Part Properties Using Surrogate Models and Multi-Objective Optimisation

In additive manufacturing (AM), due to large number of process parameters and multiple responses of interest, it is hard for AM designers to attain optimal part performance without a systematic approach. In this research, a data-driven framework is proposed to achieve the desired AM part performance and quality by predicting part properties and optimizing AM process parameters effectively and efficiently. The proposed framework encompasses efficient sampling of design space and establishing the initial experiment points. Based on established empirical data, surrogate models, are used to characterise influence of critical process parameters on responses on interest. Further, process maps can be generated for enhancing understanding on the influence of process parameters on responses of interests and AM process characteristics. Subsequently, multi-objective optimisation coupled with a multi criteria decision making technique is applied to determine an optimal design point, which maximises the identified responses of interest to meet the part functional requirements. A case study is used to validate the proposed framework for optimising an ULTEM™ 9085 fused filament fabrication part to meet its functional requirements of surface roughness and mechanical strength. From the case study, results indicate that the proposed approach is able to achieve good predictive results for responses of interest with a relatively small dataset. Further, process maps generated from the surrogate model provide a visual representation of the influence between responses of interest and critical process parameters for FFF process, which traditionally requires multiple investigations to arrive at similar conclusions.

STUDIES IN PROSPECTIVE PROCESS VALIDATION OF ALLOPURINOL USP AS ACTIVE PHARMACEUTICAL INGREDIENT

Allopurinol USP batches of same size, method, equipment and validation criterion were taken. The critical process parameter involved were reaction, drying, milling, sifting, milling, and blending stages were validation. Quality cannot be assured by daily quality control testing because of the limitations of statistical samples, and the limited facilities of finished product testing. Validation checks the accuracy and reliability of process. Aim of this work was to study prospective process validation of allopurinol USP designed to meet the current regulatory requirements and prove with assurance that the product meets the predetermined specifications and quality attributes. The critical process parameter was identified with the help of process capability and evaluated by challenging its in house and compendial specification. Three initial process validations batches APL/008, APL/009 and APL/010 were identified and evaluated as per validation master plan. The outcome indicated that this process validation data provides high degree of assurance so that manufacturing process produces a quality product.