bluuebunny/crossref_metadata_2025 huggingface dataset:
Pharmacokinetics evaluation of newly formulated beads alginate/gum acacia loaded ketoconazole in rabbit plasma by oral administration
Authors: Annisa Viviane , Sulaiman Teuku Nanda Saifullah , Nugroho Akhmad Kharis , Nugroho Agung Endro
Published: December 2023

Background and purporse: The combination of alginate and gum acacia in previous studies showed good results in inhibiting ketoconazole precipitation due to the supersaturation phenomenon. Ketoconazole-loaded alginate and gum acacia can produce hydrogel beads through cross-linking with Ca2+ using ionotropic gelation techniques. However, the pharmacokinetic study of the ketoconazole beads loaded to alginate and gum acacia needs further investigation. This study aimed to evaluate pharmacokinetic parameters using rabbits via oral administration. Experimental approach: The drug was administered orally to 2 groups of rabbits: pure ketoconazole (KTZ) and formulation of ketoconazole (AG75) groups. Blood samples were obtained from the ear marginal vein at various time points: 0 (before administration), 15, 30, 45, 60, 90, 120, 150, 180, 240, 300, 360, and 420 minutes after oral dosage. The pharmacokinetic study employed a non-compartment analysis to calculate the area under the curve (AUC), the volume of distribution (Vd F-1), clearance (Cl F-1), maximum concentration (Cmax), and time to reach maximum concentration (tmax). The data obtained from the parameter result was analyzed using the independent-sample T-test. Key result: The results of the KTZ group include AUC of 15.83±0.62 h µg mL-1, VdF-1 of 8.95±1.17 mL, ClF-1 of 3.45±0.3 mL h-1, Cmax of 4.7±0.69 µg mL-1, and tmax of 1.67±0.17 h. The results of the AG75 group include AUC of 27.8±1.01 h µg mL-1, VdF-1 of 11.5±2.4 mL, ClF-1 of 2.15±0.11 mL h-1, Cmax of 4.49±0.52 µg mL-1, and tmax of 2.5±0.5 h. Conclusion: The formulation incorporating ketoconazole beads resulted in a higher AUC0-∞ than the pure ketoconazole. This finding suggests that the created formulation has enhanced the bioavailability of ketoconazole.
Enhancing encapsulation of filarial antigen Brugia malayi thioredoxin in nano-liposomes: The role of lecithin composition
Authors: Balasubramaniyan Malathi , Vinayagam Vimalraj , Jacob Kizhakedathil Moni Philip , Perumal Kaliraj
Published: December 2023

Background and purpose: Lymphatic filariasis is a debilitating infectious disease prevalent in endemic areas, necessitating the development of an effective vaccine for eradication. Although recombinant vaccine candidates have been deemed safe, they often fail to provide sufficient protection, which can be overcome by encapsulating them in nano-liposomes. In this study, we have optimised the liposomal composition for enhanced stability and encapsulation of filarial antigen Brugia malayi thioredoxin (Bm-TRX). Experimental approach: Nano-liposomes were prepared using egg phosphatidylcholine (EPC) and cholesterol via thin-film hydration, followed by sonication and characterizing. Encapsulation efficiency was optimised using different weight ratios of EPC to cholesterol (8:2, 7:3, and 6:4) and total lipid (EPC+Cholesterol) concentration to antigen Bm-TRX (10:1, 10:2, and 10:3) followed by release kinetics study. Key results: Optimised parameters yielded spherical liposomes measuring 209 nm in diameter with narrow polydispersity. Our findings demonstrated the highest encapsulation efficiency of 70.685 % and stability of 10 hours for an EPC to cholesterol weight ratio of 7:3. The in silico study proved the antigenic nature of TRX. Conclusion: The liposomal formulations loaded with TRX, as optimized in this study, hold promise for improving antigen efficiency by enhancing stability, bioavailability, and prophylactic effects by acting as immune potentiators.
Development and evaluation of agro-waste composite for sound insulation
Authors: Amuaku Randy , K. Amanor Godwin , Adu-Gyamfi Fehrs , Amoah Asante Eric , Kweitsu Eric , Opare Samuel
Published: December 2023

The palm kernel shell is a by-product of palm kernel oil production and is commonly used in the natural biomass energy industry. Coconut husk fibre is extracted from the coconut fruit. To find a use for palm kernel shells and coconut husk fibre, a composite insulator plate was developed by the addition of a binder through a process of grinding, sieving, mixing, heating, hot-pressing and cooling in a mould. An Ahuja speaker AU60 was fixed at one end of a baffled tube and a sound level meter was placed 2 m away from the output to record sound transmission loss at 5s intervals for twenty minutes. The plates of 3, 4, 5, and, 6 mm thickness were fixed in the baffled tube at a distance of 475 mm away from the input one after the other to filter the input sound. The results showed that the setup without a composite insulator recorded the highest noise of 226.8 dB. The average recorded sound transmitted loss was 185.40, 72.47, 74.54, 76.06, and 82.85 dB for no insulator, 3, 4, 5 and, 6 mm composite insulators respectively. The introduction of the 3, 4, 5, and, 6 mm thickness composite insulators resulted in 55.3 %, 59.0 %, 59.8 % and 60.9 % reduction in noise level. The application of agro-waste composite material as a sound insulator in a baffled tube has proven to be effective by 58.7 % on average. The study has confirmed that agro-waste materials can be used in sound insulation applications.
Plantando Sementes, Colhendo Palavras
Authors: Obando Ilma Marques
Published: December 2023

A interseção entre língua portuguesa e educação ambiental oferece uma oportunidade para ampliar a compreensão dos alunos sobre questões ecológicas, incentivando a reflexão crítica e o diálogo sobre sustentabilidade, preservação ambiental e a relação entre linguagem e conscientização ecológica. Dessa forma, este artigo almeja ressaltar a importância de uma abordagem transdisciplinar, sugerindo que a conexão da Língua Portuguesa com a Educação Ambiental pode não apenas enriquecer o aprendizado dos alunos, mas também contribuir para uma consciência mais ampla e comprometida com a preservação do meio ambiente. Assim, ao unir esses domínios aparentemente distintos, este estudo destaca a relevância de abordar questões ambientais no ensino da língua portuguesa, mostrando como a conscientização ambiental pode ser promovida através da leitura, da escrita e da comunicação verbal. Além disso, defende-se que a escola deve explorar estratégias pedagógicas para desenvolver habilidades linguísticas enquanto se discute e se engaja com temas ecológicos.
CONHECIMENTO, TRATAMENTO E CONTROLE DA HIPERTENSÃO ARTERIAL EM INDÍVIDUOS ADULTOS CADASTRADOS NA ESTRATÉGIA SAÚDE DA FAMÍLIA DE MUCUGÊ, BAHIA
Authors: Tapioca Thatiane Silva Costa , Ferreira Débora Pinheiro Alves , Goís Joselice Almeida , Nascimento Mônica de Andrade , Rodrigues Éder Pereira , Nascimento Sobrinho Carlito Lopes
Published: December 2023

Introdução: A Hipertensão Arterial Sistêmica (HAS) é uma doença crônica não transmissível, apresenta taxas de controle insatisfatórias no Brasil e configura-se como um relevante desafio para a saúde pública. Objetivo: estimar a prevalência de hipertensão referida, o uso referido de medicação anti-hipertensiva e a taxa de controle da pressão arterial, em indivíduos adultos cadastrados na Estratégia Saúde da Família de Mucugê, Bahia. Metodologia: estudo descritivo em uma amostra aleatória de 337 indivíduos com idade ≥ 18 anos, cadastrada na Estratégia Saúde da Família do município de Mucugê, Bahia. Foram coletados dados sociodemográficos, relato de diagnóstico de HAS e uso de medicação anti-hipertensiva e foi realizada também a aferição da pressão arterial para a verificação da taxa de controle. Resultados: entre os estudados 35,3% apresentaram HAS autorreferida, desses 94,11% faziam uso de medicação anti-hipertensiva. A maior parte 66,1% dos indivíduos que referiram uso de medicação anti-hipertensiva estavam com os níveis pressóricos alterados no momento da entrevista. Considerações Finais: Observou-se elevada prevalência de HAS e uso anti-hipertensivo, porém com baixa taxa de controle dos níveis pressóricos. Os resultados apontam para a necessidade de ações de vigilância em saúde e incentivo a adoção de estilo de vida saudável e adesão ao tratamento; sendo essas ações possíveis e mais eficazes com a valorização da atenção primária.
Russian-Ukrainian Conflict: International Humanitarian Law and Civilian Settlements
Authors: Gunawan Yordan , Gultom Qinnara Zegia , Amarulia Shafirah , Arumbinang Mohammad Hazyar
Published: December 2023

The research analyzes the views of the International Humanitarian Law (IHL) and UN Charter violations in the case of the invasion of civilian settlements in the Russia-Ukraine conflict for justice. The conflict, which took place on February 24, 2022, has raised serious concerns about violations of the UN Charter and IHL and the protection of civilians. This research collected data and information from various primary and secondary sources, including reports of international organizations, legal documents, and journal analysis. A qualitative approach was used to analyze the impact of the invasion of civilian settlements on IHL in the case of the Russia and Ukraine case. The results show that the view of IHL in the context of the invasion of civilian settlements in the Russia-Ukraine case has caused great harm to civilians, ranging from damage to homes, infrastructure, and public facilities, including casualties. It also appears that Russia has ignored the guiding principles of the UN Charter. To overcome this problem, several steps can be taken. First, there is a need to increase understanding and awareness of IHL among all parties involved in the conflict. Second, increase efforts to maintain brotherhood between nations. Third, working together to assist in humanitarian terms in the event of armed conflict, famine, and starvation. The resulting policy implications and recommendations can be used as a guide for policymakers and practitioners to improve the humanitarian protection of civilians in the future.
ANALISIS PERHITUNGAN HARGA POKOK PRODUKSI DENGAN MENGGUNAKAN METODE FULL COSTING SEBAGAI DASAR PENENTUAN HARGA JUAL PADA PERUSAHAAN AVARA DESIGN
Authors: Nugroho Tulus Pujo
Published: December 2023

Bagi pemilik usaha memperoleh laba merupakan tujuan utama untuk kelangsungan hidup dan kemajuan usaha itu sendiri. Terdapat tiga faktor utama yang harus diperhatikan dalam target penentuan laba, yaitu jumlah barang yang harus diproduksi, biaya produksi perunit untuk memproduksi dan penentuan harga jual perunit produk tersebut. Untuk mencapai laba yang optimal, harga pokok produksi harus diupayakan dapat ditekan seminimal mungkin. Adapun tujuan dari penulisan ilmiah ini adalah: Untuk menghitung harga pokok produksi yang ditetapkan oleh pemilik Perusahaan dengan metode full costing dan mengetahui perbandingan antara perhitungan harga pokok produksi yang diterapkan oleh perusahaan dengan metode full costing terhadap harga jual. Metode yang dilakukan menggunakan teknik penelitian deskriptif kuantitatif. Menurut perhitungan perusahaan biaya non-produksi tidak dihitung untuk pembebanan terhadap pesanan, sedangkan menurut metode full costing biaya non-produksi termasuk kedalam pembebanan biaya pesanan yaitu Biaya Pengangkutan sebesar Rp 1.000.000,-.
SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction
Authors: Alam Mahbub Ul , Hollmén Jaakko , Baldvinsson Jón Rúnar , Rahmani Rahim
Published: December 2023

The interpretability of deep neural networks has become a subject of great interest within the medical and healthcare domain. This attention stems from concerns regarding transparency, legal and ethical considerations, and the medical significance of predictions generated by these deep neural networks in clinical decision support systems. To address this matter, our study delves into the application of four well-established interpretability methods: Local Interpretable Model-agnostic Explanations (LIME), Shapley Additive exPlanations (SHAP), Gradient-weighted Class Activation Mapping (Grad-CAM), and Layer-wise Relevance Propagation (LRP). Leveraging the approach of transfer learning with a multi-label-multi-class chest radiography dataset, we aim to interpret predictions pertaining to specific pathology classes. Our analysis encompasses both single-label and multi-label predictions, providing a comprehensive and unbiased assessment through quantitative and qualitative investigations, which are compared against human expert annotation. Notably, Grad-CAM demonstrates the most favorable performance in quantitative evaluation, while the LIME heatmap score segmentation visualization exhibits the highest level of medical significance. Our research underscores both the outcomes and the challenges faced in the holistic approach adopted for assessing these interpretability methods and suggests that a multimodal-based approach, incorporating diverse sources of information beyond chest radiography images, could offer additional insights for enhancing interpretability in the medical domain.
Location Privacy Protection and Coverage Hole Effects in Event Monitoring Wireless Networks for Internet of Things Applications
Authors: Mutalemwa Lilian
Published: December 2023

Source-location privacy (SLP) protection improves security in event monitoring wireless sensor networks (WSNs) for Internet of Things (IoT) applications. However, due to constrained energy resources, WSNs incur coverage holes that affect the level of SLP protection. Existing studies have ineffectively analysed the effects of coverage holes on SLP protection. Noting the limitation, this study investigated the coverage hole effects. Performance of various SLP routing protocols was evaluated based on the sensor node utilization ratio, attack success rate, end-to-end delay, and packet delivery ratio. Then, considering the challenge of limited battery power in IoT sensors, the performance gains and limitations of the protocols were identified. Simulation results demonstrate that the data dissemination SLP routing protocol (DIRP) outperforms other protocols. However, the performance of DIRP is significantly affected by coverage holes. The results suggest that for DIRP to be viable in IoT applications, the integration of distributed energy resources should be considered.
PERSPEKTIF EKONOMI DAN BISNIS ISLAM MENGENAI PENGARUH INDEKS PEMBANGUNAN MANUSIA, TINGKAT KEMISKINAN, DAN BELANJA MODAL TERHADAP PENGANGGURAN TERBUKA DI JAWA BARAT TAHUN 2002-2021
Authors: Puloh  , Rifai Muhamad , Faiz Marcelino , Putri Hani Cahyani
Published: December 2023

Penelitian ini bertujuan untuk menunjukkan dampak Indeks Pembangunan Manusia, kemiskinan, belanja modal terhadap tingkat pengangguran terbuka di Provinsi Jawa Barat tahun 2002-2021. Akumulasi data menggunakan data sekunder Indeks Pembangunan Manusia, tingkat kemiskinan dan belanja modal di Provinsi Jawa Barat yang diperoleh dari Badan Pusat Statistik berupa data time series tahun 2002 sampai dengan tahun 2021. Metode analisis yang digunakan dalam penelitian ini adalah metode analisis regresi berganda yang terdiri dari lebih dari satu variabel independen, diolah dengan menggunakan aplikasi SPSS 26, menghasilkan persamaan regresi untuk IPM = - 0,019 ; MSK = 0,793 ; BM = - 0,034. Hasil penelitian ini menunjukkan bahwa variabel IPM berpengaruh negatif signifikan terhadap tingkat pengangguran terbuka. Sedangkan variabel belanja modal berpengaruh negatif dan tidak signifikan terhadap tingkat pengangguran terbuka.
ANALISIS PERBANDINGAN KINERJA KARYAWAN PT. PLN (PERSERO) ULP CILEDUG SEBELUM DAN MASA PANDEMI COVID-19 DALAM SUDUT PANDANG MANAJEMEN SYARIAH
Authors: Riyani Desti Amanda , Suryani Ermi , Shiddieqy Hasbi Ash
Published: December 2023

Selama pandemi Covid-19, terjadi perubahan signifikan di berbagai bidang. Salah satunya adalah dalam bidang ekonomi, di mana hampir semua perusahaan melakukan perubahan dalam aktivitas mereka. Salah satu aktivitas perusahaan dalam merespons pandemi ini adalah melakukan WFH (Work From Home). Di dalam sebuah perusahaan, sumber daya manusia merupakan sumber daya yang paling berpengaruh. Keberhasilan perusahaan dalam menjalankan aktivitasnya dipengaruhi oleh kinerja karyawan. Tujuan dari penelitian ini adalah untuk menentukan dan membandingkan kondisi kinerja karyawan PT. PLN (Persero) ULP Ciledug sebelum dan selama pandemi Covid-19, serta untuk mengetahui pandangan manajemen syariah terhadap kinerja karyawan PT. PLN (Persero) ULP Ciledug sebelum dan selama pandemi Covid-19. Jenis penelitian yang digunakan adalah deskriptif kualitatif, yang bertujuan untuk menganalisis data yang diperoleh dan kemudian membuat kesimpulan. Sumber data diperoleh melalui sumber data primer dan sekunder menggunakan metode pengumpulan data wawancara dan dokumentasi di PT. PLN (Persero) ULP Ciledug, yaitu dari Sistem Informasi Manajemen Kinerja Pegawai (SIMKPNAS). Hasil dan analisis yang diperoleh dari penelitian ini adalah adanya perbedaan dalam kinerja karyawan PT. PLN (Persero) ULP Ciledug sebelum pandemi Covid-19. Kinerja karyawan yang diukur melalui key performence indicator (KPI) sangat baik, di mana rata-rata karyawan di PT. PLN (Persero) ULP Ciledug berada pada kompetensi 2 atau dalam kategori "Melebihi Harapan" Memenuhi Persyaratan (ER). Sementara itu, selama pandemi Covid-19, terjadi penurunan rata-rata dalam kompetensi 2 dan 3 atau dalam kategori "Melebihi Harapan" Melebihi Persyaratan (ER) dan "Memenuhi Persyaratan" (MR), yang berarti terjadi penurunan kinerja karyawan PT. PLN (Persero) ULP Ciledug selama pandemi Covid-19. Dan kinerja karyawan PT. PLN (Persero) ULP Ciledug sebelum dan selama pandemi Covid-19 dari perspektif manajemen syariah telah dilaksanakan dengan baik sesuai dengan syariah Islam.
Multi-Active Method (MAM) for the Analysis of Agriculture Product Technical Ingredients and Formulated Products
Authors: Garvey Jim , Nováková Olga , Pigeon Olivier , McNally Mary
Published: December 2023

In regulatory laboratories, where potentially hundreds of different types of sample and active ingredients can be evaluated every year, a unique set of conditions provided by agricultural product manufacturers in their regulatory methods are faced with the decision to purchase a new and different analytical column or not follow the enforcement method provided by the manufacturer. Because of this, a multi-analyte method has been developed at the Irish Department of Agriculture, Food and The Marine, contributed to by the regulatory laboratories in Belgium and the Czech Republic, analyzing more than 70 active ingredients using high performance liquid chromatography (HPLC) and more than 35 active ingredients by ultrahigh-pressure liquid chromatography (UHPLC).. The method has been designed for use by quality control laboratories and is suitable for determining a range of active substances in a wider range of formulated products as well as the technical AI itself. The method has been validated for linearity, precision, accuracy, and specificity for seven technical active ingredients as defined by FMC Corporation. The method and results are described in this article.
Kehidupan Sosial Ekonomi Tukang Becak Terhadap Keberadaan Ojek Online di Jember
Authors: Andini Istiqomah  , Ning Nabila Zuhro  , Shalfian Agung Prasetyo
Published: December 2023

Penelitian ini mengkaji dampak keberadaan layanan ojek online terhadap kondisi kehidupan sosial ekonomi tukang becak di daerah Jalan Wijaya Kusuma, Kecamatan Patrang, Kabupaten Jember. Pendekatan fenomenologi digunakan dengan melibatkan tiga tukang becak sebagai subjek penelitian. Hasil wawancara menunjukkan bahwa persaingan dengan ojek online telah menyebabkan penurunan pendapatan bagi tukang becak, yang pada gilirannya membuat mereka kesulitan memenuhi kebutuhan sehari-hari. Faktor-faktor seperti tingginya persaingan, perubahan preferensi konsumen, dan kurangnya peluang kerja lain mempengaruhi kondisi sosial ekonomi tukang becak. Kajian sosiologis menyoroti kompleksitas interaksi antara faktor-faktor sosial dan ekonomi yang memengaruhi kehidupan para tukang becak, dengan fokus pada latar belakang ekonomi, pendidikan, lingkungan tempat tinggal, distribusi pendapatan, ketidaksetaraan ekonomi, dan dampak perubahan ekonomi seperti munculnya ojek online. Tantangan yang dihadapi tukang becak dalam menyesuaikan diri dengan kemajuan teknologi, terutama kehadiran ojek online, juga disorot. Sebagai solusi, penelitian menyarankan pencarian sumber pendapatan tambahan, manajemen keuangan keluarga yang lebih cermat, kerja sama antara tukang becak dan pengemudi ojek online, dukungan dan pelatihan dari pemerintah, serta kerjasama dengan pihak swasta dan LSM untuk membantu tukang becak menghadapi persaingan dengan ojek online.
Qualidade de Software para Engenheiros de IA: Um Estudo Inicial da Realidade Brasileira
Authors: Silva Lidiane C. , Fernandes Lucinara K. S. , Soares Eder F. , Maia Paulo Henrique M. , Santos Ismayle S. , Oliveira Francisco C. M. B.
Published: December 2023

This article presents an analysis of the Brazilian reality regarding software quality for Artificial Intelligence (AI). The study seeks to investigate the software quality assurance strategies adopted during the lifecycle of AI/ML components, covering the development, integration and maintenance phases. We conducted a survey with 40 participants, and the results indicate that the Brazilian industry faces several quality issues in the development of AI systems, including accuracy, performance, interpretability and scalability. In addition, challenges related to maintainability, documentation, reuse and code quality are identified.
Machine Learning for the Identification and Classification of Technical Debt Types on StackOverflow Discussions
Authors: Gama Eliakim , Cortés Mariela I. , Paixao Matheus , Damasceno Adson
Published: December 2023

In today’s fast-paced software industry, understanding and managing Technical Debt (TD) is crucial for software development. TD can compromise the long-term quality of software systems. The occurrence of TD is commonly reported and discussed by practitioners on Question and Answers (Q&A) platforms, such as Stack Overflow (SO). Data from Q&A platforms has been leveraged by the TD research community, most prominently regarding knowledge extraction. However, manual analyses of such data not only require considerable effort but also suffer from biases. Hence, this paper aims to propose an automated approach for identifying and classifying types of TD in SO discussions using machine learning (ML) and natural language processing. We divided our methodology into four main steps: i) data preprocessing, ii) application of natural language processing, iii) application of ML algorithms, and iv) computing the evaluation metrics for the proposed models. Our results indicate that ML algorithms have the potential to be successfully applied to automatically identify and classify TD types on SO discussions.We achieved a recall of 85% for test debt and a precision of 78% for design debt. Furthermore, the results of automated TD identification on SO benefit the software development community by enhancing solution quality, raising awareness of best practices, and facilitating collaboration among developers. This leads to more efficient development and the promotion of consistent standards. We make our entire dataset and pre-trained models available to encourage future research directions.
Adherence to Exercise Training and Physical Function in Older Adults Diagnosed with Knee Osteoarthritis
Authors: Nogueira Raquel , Moura Jodean , Costa Cyrene , Novais Tânia Maria , Oliveira Paula de Lourdes , Ribeiro Maria Jacqueline , Maduro Paula Andreatta , Almeida Fabiano de Jesus , Soares Stela , Schwingel Paulo Adriano , Bavaresco Gambassi Bruno
Published: December 2023

Background
Knee osteoarthritis (KOA) provokes pain, muscle weakness, and consequent impairment in activities of daily living. On the other hand, adherence to exercise training (ET) is associated with the attenuation of the impairments. The aims of the present study were to a) investigate adherence to ET in older adults with KOA diagnosed attending public service; and b) to analyze the physical function of the older adults with KOA who did not adhere to the ET in public service.
Methods
The adherence to ET programs was analyzed retrospectively from each patient’s date of KOA diagnosis. After assessing the adherence to ET, the physical function of these older adults diagnosed with KOA (n=19) was analyzed and compared with another group composed of asymptomatic sedentary older adults without evidence of KOA (ASKOA) (n=17).
Results
Although all older adults with KOA received guidelines to practice ET, only 58% were able to start a program. Additionally, 100% of the sample could not perform ET uninterruptedly. According to the findings, close to 80% of older adults had difficulties scheduling ET sessions in public places. Subjects with KOA (12.1±3.1; IC95%:10.6–13.6) had worse lower limb functional capacity than ASKOA (8.1±1.0; IC95%:7.6–8.6; p<.001; δ=4.0 sec; d=1.7). Likewise, they had a lower dynamic balance than KOA (12.4±2.7; IC95%:11.1–13.7 vs. 8.0±1.1; IC95%:7.4–8.6; p<.001; δ=4.4 sec; d=2.1).
Conclusions
The investigated sample has a lack of ET adherence by difficulties in scheduling ET sessions in public places. In addition, it demonstrated impairment in physical function in older adults with KOA.
Hymni et Sequentiae
Authors: Bonnus Hermann
Published: December 2023

The book HYMNI ET SEQVENTIÆ published in Lübeck by Georg Richoff in 1559 contains not only the two advertised genres of hymns and sequences but also further liturgical forms, a monophonic repertoire for daily services in Latin Schools. The pieces appear according to the order of the liturgical year including the many feast-days (such as those of the Apostles) – a glimpse into the astonishing variety of the exercitium quotidianum, the daily exercises in Bible-reading and singing practice for the school choir, which had never before been identifiable in this detail. The compiler was Hermann Bonnus, who had studied with Luther and Melanchthon, was a colleague of Bugenhagen, the first Rector of the Catharineum in Lübeck in 1531 and Superintendent in the city in 1532, and also editor who revised the titles in the work in the spirit of Reformation theology or on the basis of Biblical texts (Bonnus correxit). This collection is an important document of the reception of the old church liturgy by the young evangelical protestant church. The only surviving copy in Germany is believed to have been lost since 1945, but recently an original copy was found in the Royal Library in Stockholm and has been used for this reprint.
Idiopathic Intracranial Hypertension
Authors: Kostic Maja , Colvin Elizabeth , Duy Huynh , Ro Sarah , Quinsey Carolyn , Shevtsova Inga , Machineni Sriram
Published: December 2023

Idiopathic intracranial hypertension (IIH), also known as pseudotumor cerebri, is a condition marked by increased cerebrospinal (CSF) pressure in the absence of secondary causes, such as brain tumors, venous sinus thrombosis, and meningitis. The exact cause of IIH is unknown, but the rise in intracranial pressure (ICP) is a defining characteristic leading to the clinical presentation of headaches, transient visual obscurations, pulsatile tinnitus, and retrobulbar pain. This text aims to discuss IIH and the effectiveness of a multi-disciplinary approach, emphasizing collaboration by neuro-ophthalmology, neurology, neurosurgery, radiology, oculoplastic, and weight loss teams to achieve clinical remission of IIH. Literature was reviewed to discuss aspects of IIH in the pediatric population, and our clinical experience was utilized to provide recommendations regarding the importance of a multi-disciplinary team. This chapter explores IIH in the pediatric population regarding its demographics, clinical manifestations, potential underlying pathophysiology, diagnostic steps, and the importance of a multi-disciplinary approach to management, as it is the most optimal. This allows patients to receive comprehensive care that will address more aspects of IIH while also maintaining long-term goals and remission.
Perspective Chapter: The Impacts of Maternal Imprisonment on Children
Authors: Arrondelle Donna , Gadian Naomi , Plugge Emma
Published: December 2023

Taking a global perspective, this chapter examines socio-economic and health and wellbeing impacts on children with experience of maternal imprisonment. Whilst we know the approximate numbers of women and girls imprisoned is approximately 6.9% of the global prison population there is no official recording of how many children lose their primary caregiver when women are imprisoned. Although estimates suggest the majority of imprisoned women are mothers. Drawing upon secondary data, we reveal the global knowledge base on the impacts of maternal imprisonment on children is incredibly limited with most understanding drawn from the US. The extant literature shows that children with experience of maternal imprisonment lose essential economic and social capital associated with educational deficits and suffer a range of physical and mental health risk factors. Responding to the evidence we draw six distinct conclusions and argue that for reductions in the various harms outlined separation of mother–child should be a last resort. We make the case for community-based residential alternatives to custodial sentencing for women with accompanying monitoring and evaluation to ameliorate the negative socio-economic and health and wellbeing impacts associated with this form of maternal deprivation.
Innovative Greenhouse to Improve Economic and Environmental Conditions
Authors: Abdel Mo’ez Mansour Embaby Zainab
Published: December 2023

Together with the World Bank and the Food and Agriculture Organization (FAO), a number of international organizations are promoting innovation in agricultural systems to combat natural disasters like extreme weather, drought, floods, rising sea levels, increased snowmelt, and changes in the amount and timing of water used for irrigation. The impacts of climate change on food security are undeniably significant, and they are expected to get worse over the coming years as a result of population growth, economic development, urbanization, and the recurrence of natural disasters. In today’s agribusiness, particularly horticultural agribusinesses such as vegetables and decorative plants, climate-smart greenhouse is not a novel concept. In terms of GHG (greenhouse gas) emissions, CSA (Climate Smart Agriculture) can contribute. These days, climate-smart greenhouse (CSG) can actually connect adaptation and mitigation at all scales and helps farmers take the lead in combating climate change. The research on CSG emphasizes the need for innovative thinking to harmonize policy and practices in a way that is complementary. Additionally, CSG has to have a better grasp of how well-equipped the consultants or extension services are in each nation to assist with training farmers in climate-smart practices. Additionally, new financial tools are required to enable global, national, and local transformations.
Advances in Sustainable Palm Oil Milling Technologies: Enhancing Efficiency and Environmental Performance
Authors: Onn Hong Wai
Published: December 2023

This chapter conducts a thorough examination of current and emerging palm oil milling technologies, emphasizing their role in enhancing efficiency while addressing environmental concerns. Structured into four sections, it begins by evaluating traditional milling methods and equipment, considering their effectiveness and environmental impact in sterilization, threshing, digestion, and oil clarification. The subsequent section explores cutting-edge advancements, including automation and biotechnology applications for improved efficiency and resource optimization. The third section focuses on initiatives to reduce carbon emissions, highlighting technologies for enhanced energy efficiency, renewable energy integration, and improved waste management. Lastly, the chapter delves into the concept of a circular economy in the palm oil industry, emphasizing waste reduction, resource optimization, and sustainable practices throughout the palm oil production process. It discusses biomass utilization, by-product valorization, and integrated palm oil biorefineries as essential elements of circular economy approaches. This comprehensive exploration aims to familiarize readers with Elaeis guineensis and advocate for a more sustainable future in the palm oil industry, providing a thorough understanding of contemporary milling technologies and their potential to mitigate environmental impact.
Classification of HHO-based Machine Learning Techniques for Clone Attack Detection in WSN
Authors:   School of Computer Science and Engineering, VIT-AP University, Vijayawada-522237, India, Vatambeti Ramesh , Damera Vijay Kumar , H. Karthikeyan , M. Manohar , Priya C. Sharon Roji , Mekala M. S.
Published: December 2023

Thanks to recent technological advancements, low-cost sensors with dispensation and communication capabilities are now feasible. As an example, a Wireless Sensor Network (WSN) is a network in which the nodes are mobile computers that exchange data with one another over wireless connections rather than relying on a central server. These inexpensive sensor nodes are particularly vulnerable to a clone node or replication assault because of their limited processing power, memory, battery life, and absence of tamper-resistant hardware. Once an attacker compromises a sensor node, they can create many copies of it elsewhere in the network that share the same ID. This would give the attacker complete internal control of the network, allowing them to mimic the genuine nodes' behavior. This is why scientists are so intent on developing better clone assault detection procedures. This research proposes a machine learning based clone node detection (ML-CND) technique to identify clone nodes in wireless networks. The goal is to identify clones effectively enough to prevent cloning attacks from happening in the first place. Use a low-cost identity verification process to identify clones in specific locations as well as around the globe. Using the Optimized Extreme Learning Machine (OELM), with kernels of ELM ideally determined through the Horse Herd Metaheuristic Optimization Algorithm (HHO), this technique safeguards the network from node identity replicas. Using the node identity replicas, the most reliable transmission path may be selected. The procedure is meant to be used to retrieve data from a network node. The simulation result demonstrates the performance analysis of several factors, including sensitivity, specificity, recall, and detection.
Evaluation of WATERMARK Channel for Underwater Communication using Dual Tree Complex Wavelet Transform based Orthogonal Frequency Division Multiplexing Model
Authors:   Department of Electronics, BMS College of Engineering, Visvesvaraya Technological University, Bengaluru-560019, Karnataka, India, Nanjareddy Girish , Boregowda Veena M. , Maroof Naeem
Published: December 2023

Underwater communication is one of the important research areas which involves design and development of communication systems that can demonstrate high data rate and low Bit Error Rate (BER). In this work three different modulation schemes are compared for their performances in terms of BER and Peak to Average Power Ratio (PAPR). The realistic channel model called WATERMARK is used as a benchmark to evaluate channel performances. The mathematical model is developed in MATLAB and channel environments such as Norway Oslo fjord (NOF1), Norway Continental Shelf (NCS1), Brest Commercial Harbour (BCH1), Kauai (KAU1, KAU2) are considered for modelling different underwater channels. The data symbols are modulated using Dual Tree Complex Wavelet Transform (DTCWT) Orthogonal Frequency Division Multiplexing (OFDM) model to generate multi subcarriers and are demodulated at the receiver considering underwater channel environments. The BER results are evaluated for channel depth less than 10m and 10-50m. An improvement of 2x10-2 in terms of BER is observed when compared with Fast Fourier Transform (FFT) based OFDM model.
An Optimized Authentication Mechanism for Mobile Agents by Using Machine Learning
Authors:   JSS Academy of Technical Education, Noida /Department of Computer Science and Engineering, Uttar Pradesh, 201301, India, Kumar Pradeep , Singhal Niraj , Asim Mohammad , Vatsa Avimanyou
Published: December 2023

A mobile agent is a small piece of software which works on direction of its source platform on a regular basis. Because mobile agents roam around wide area networks autonomously, the protection of the agents and platforms is a serious worry. The number of mobile agents-based software applications has increased dramatically over the past year. It has also enhanced the security risks associated with such applications. Most of the security mechanisms in the mobile agent architecture focus solely on platform security, leaving mobile agent safety to be a significant challenge. An efficient authentication scheme is proposed in this article to address the situation of protection and authentication of mobile agent at the hour of migration of across multiple platforms in malicious environment. An authentication mechanism for the mobile agent based on the Hopfield neural network proposed. The mobile agent’s identity and password are authenticate using the specified mechanism at the moment of execution of assigned operation. An evaluative assessment has been offered, along with their complex character, in comparison to numerous agent authentication approaches. The proposed method has been put into practice, and its different aspects have been put to the test. In contrasted to typical client-server and code-on-demand approaches, the analysis shows that computation here is often more safe and simpler.
A Cryptographic based I2ADO-DNN Security Framework for Intrusion Detection in Cloud Systems
Authors:   Department of Computer Science and Engineering, Sathyabama institute of science and technology, Chennai, Tamilnadu, India, Muneera M. Nafees , Selvi G. Anbu , Vaissnave V. , Rajora Gopal Lal
Published: December 2023

Cloud computing's popularity and success are directly related to improvements in the use of Information and Communication Technologies (ICT). The adoption of cloud implementation and services has become crucial due to security and privacy concerns raised by outsourcing data and business applications to the cloud or a third party. To protect the confidentiality and security of cloud networks, a variety of Intrusion Detection System (IDS) frameworks have been developed in the conventional works. However, the main issues with the current works are their lengthy nature, difficulty in intrusion detection, over-fitting, high error rate, and false alarm rates. As a result, the proposed study attempts to create a compact IDS architecture based on cryptography for cloud security. Here, the balanced and normalized dataset is produced using the z-score preprocessing procedure. The best attributes for enhancing intrusion detection accuracy are then selected using an Intelligent Adorn Dragonfly Optimization (IADO). In addition, the trained features are used to classify the normal and attacking data using an Intermittent Deep Neural Network (IDNN) classification model. Finally, the Searchable Encryption (SE) mechanism is applied to ensure the security of cloud data against intruders. In this study, a thorough analysis has been conducted utilizing various parameters to validate the intrusion detection performance of the proposed I2ADO-DNN model.
Network Traffic Prediction with Reduced Power Consumption towards Green Cellular Networks
Authors:   D. Y. Patil institute of Technology, Pimpri, Pune-411018, India, Rajule Nilakshee , Venkatesan Mithra , Menon Radhika , Kulkarni Anju
Published: December 2023

The increased number of cellular network subscribers is giving rise to the network densification in next generation networks further increasing the greenhouse gas emission and the operational cost of network. Such issues have ignited a keen interest in the deployment of energy-efficient communication technologies rather than modifying the infrastructure of cellular networks. In cellular network largest portion of the power is consumed at the Base stations (BSs). Hence application of energy saving techniques at the BS will help reduce the power consumption of the cellular network further enhancing the energy efficiency (EE) of the network. As a result, BS sleep/wake-up techniques may significantly enhance cellular networks' energy efficiency. In the proposed work traffic and interference aware BS sleeping technique is proposed with an aim of reducing the power consumption of network while offering the desired Quality of Service (QoS) to the users. To implement the BS sleep modes in an efficient manner the prediction of network traffic load is carried out for future time slots. The Long Short term Memory model is used for prediction of network traffic load. Simulation results show that the proposed system provides significant reduction in power consumption as compared with the existing techniques while assuring the QoS requirements. With the proposed system the power saving is enhanced by approximately 2% when compared with the existing techniques. His proposed system will help in establishing green communication networks with reduced energy and power consumption.
Energy Based Route Prioritization for Optimum Multi-path Selection
Authors:   Kurukshetra University, Kurukshetra, India, Atri Swati , Tyagi Sanjay
Published: December 2023

Energy–aware routing in wireless ad hoc networks is one of the demanding fields of research. Nodes of the network are battery operated that are difficult to recharge and replace, that's why while developing a routing protocol energy consumption metric should always be at high priority. Nodes of mobile ad hoc networks are distributed in different directions forming arbitrary topology instantly. To propose an energy-efficient routing protocol for such a dynamic, self-organized, self-configured, and self-controlled network is certainly a challenge and an open research problem. Energy constraints and mobility leading to link breakage are the motivating factors behind the development of the proposed Optimized Priority-based Ad Hoc on Demand Multi-path Distance Vector Energy Efficient Routing Protocol (OPAOMDV-EE). The routing protocol added three fields (CE, MAX_E, MIN_E) to the traditional AOMDV RREQ and RREP packets, which are further used for calculating total priority field value. This value is used by the source node for selecting an optimal prioritized energy-efficient route. The proposed OPAOMDV-EE protocol has been simulated on Network Simulator-2 (NS-2) for two different scenarios that prove the effectiveness of OPAOMDV-EE in terms of various performance metrics with reduced energy consumption.
The Security of Blockchain-based Electronic Health Record: A Systematic Review
Authors:   School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India, Exceline C. Eben , Nagarajan Sivakumar
Published: December 2023

The healthcare industry makes rampant strides in sharing electronic health records with upgraded efficiency and delivery. Electronic health records comprise personal and sensitive information of patients that are confidential. The current security mechanism in cloud computing to store and share electronic health records results in data breaches. In the recent era, blockchain is introduced in storing and accessing electronic health records. Blockchain is utilized for numerous applications in the healthcare industry, such as remote patient tracking, biomedical research, collaborative decision making and patient-centric data sharing with multiple healthcare providers. In all circumstances, blockchain guarantees immutability, data privacy, data integrity, transparency, interoperability, and user privacy that are strictly required to access electronic health records. This review paper provides a systematic study of the security of blockchain-based electronic health records. Moreover, based on thematic content analysis of various research literature, this paper provides open challenges in the blockchain-based electronic health record.
Plant Disease Detection Using Deep Learning
Authors:   Faculty of Computers and Information Menoufia University / Computer Science / Shebin Elkom, 32511, Egypt, Hamed Bahaa S. , Hussein Mahmoud M. , Mousa Afaf M.
Published: December 2023

Agricultural development is a critical strategy for promoting prosperity and addressing the challenge of feeding nearly 10 billion people by 2050. Plant diseases can significantly impact food production, reducing both quantity and diversity. Therefore, early detection of plant diseases through automatic detection methods based on deep learning can improve food production quality and reduce economic losses. While previous models have been implemented for a single type of plant to ensure high accuracy, they require high-quality images for proper classification and are not effective with low-resolution images. To address these limitations, this paper proposes the use of pre-trained model based on convolutional neural networks (CNN) for plant disease detection. The focus is on fine-tuning the hyperparameters of popular pre-trained model such as EfficientNetV2S, to achieve higher accuracy in detecting plant diseases in lower resolution images, crowded and misleading backgrounds, shadows on leaves, different textures, and changes in brightness. The study utilized the Plant Diseases Dataset, which includes infected and uninfected crop leaves comprising 38 classes. In pursuit of improving the adaptability and robustness of our neural networks, we intentionally exposed them to a deliberately noisy training dataset. This strategic move followed the modification of the Plant Diseases Dataset, tailored to better suit the demands of our training process. Our objective was to enhance the network's ability to generalize effectively and perform robustly in real-world scenarios. This approach represents a critical step in our study's overarching goal of advancing plant disease detection, especially in challenging conditions, and underscores the importance of dataset optimization in deep learning applications.
Decoding Optimization Algorithms for Convolutional Neural Networks in Time Series Regression Tasks
Authors:   India Meteorological Department, MoES, Visakhapatnam, India, Singh Deep Karan , Rawat Nisha
Published: December 2023

Optimization algorithms play a vital role in training deep learning models effectively. This research paper presents a comprehensive comparative analysis of various optimization algorithms for Convolutional Neural Networks (CNNs) in the context of time series regression. The study focuses on the specific application of maximum temperature prediction, utilizing a dataset of historical temperature records. The primary objective is to investigate the performance of different optimizers and evaluate their impact on the accuracy and convergence properties of the CNN model. Experiments were conducted using different optimizers, including Stochastic Gradient Descent (SGD), RMSprop, Adagrad, Adadelta, Adam, and Adamax, while keeping other factors constant. Their performance was evaluated and compared based on metrics such as mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), R-squared (R²), mean absolute percentage error (MAPE), and explained variance score (EVS) to measure the predictive accuracy and generalization capability of the models. Additionally, learning curves are analyzed to observe the convergence behavior of each optimizer. The experimental results, indicating significant variations in convergence speed, accuracy, and robustness among the optimizers, underscore the research value of this work. By comprehensively evaluating and comparing various optimization algorithms, we aimed to provide valuable insights into their performance characteristics in the context of time series regression using CNN models. This work contributes to the understanding of optimizer selection and its impact on model performance, assisting researchers and practitioners in choosing the most suitable optimization algorithm for time series regression tasks.