bluuebunny/crossref_metadata_2025 huggingface dataset:
Intracranial epidermoid cysts: Demographics, surgical strategies, and postoperative outcomes in a retrospective cohort study
Authors: Faraj Moneer K.
Published: January 2025

Background:

Intracranial epidermoid cysts are infrequent, benign, and slow-growing lesions derived from ectodermal vestiges. Although extremely uncommon, these lesions represent a great challenge from a diagnostic and surgical point of view because they are located close to major neurovascular structures with great potential for complications. Our work aims to analyze demographic, clinical, radiological, and surgical features in patients with intracranial epidermoid cysts and to assess post-surgical outcomes to define better management strategies.

Methods:

We conducted a retrospective cohort study of patients diagnosed with histologically confirmed intracranial epidermoid cysts and treated surgically at Dr. Said Al-Witry’s Neuroscience Hospital from January 2020 to September 2024. Demographic data, clinical presentations, imaging findings, surgical approaches, and postoperative complications were analyzed using descriptive statistics and Chi-square tests. Statistical significance was set at P < 0.05.

Results:

Out of 40 patients, 75% were male, with headaches being the most common symptom (50%). Magnetic resonance imaging (MRI) findings demonstrated T1 hypo-intensity in 95% and T2 hyper-intensity in all cases. The retrosigmoid approach was the most frequently employed surgical method (60%), followed by frontotemporal (30%) and midline suboccipital (10%) approaches. Postoperative complications occurred in 35% of cases, including facial nerve palsy (15%), aseptic meningitis (10%), cerebrospinal fluid leaks (5%), and hydrocephalus (5%). Chi-square analysis showed significant associations between surgical approaches and postoperative complications (P = 0.048).

Conclusion:

Intracranial epidermoid cysts show a high incidence in males and present mostly with nonspecific symptoms such as headaches and seizures. MRI remains the key investigation modality. The retrosigmoid approach shows less complication rate when compared to other techniques. Even though surgery has evolved, complications such as meningitis and nerve palsy persist, so much attention to detail is required in preoperative planning and follow-up in the long run for optimum outcomes for the patients.
Immunoexcitoxicity as the possible major pathophysiology behind multiple sclerosis and other autoimmune disorders
Authors: Blaylock Russell L.
Published: January 2025

Autoimmune disorders are destructive processes considered to be an attack on “self ” antigens by the immune system CD-+4 T-cells that are directed toward antigens, in the case of multiple sclerosis (MS), particularly myelin antigens. Yet, there is growing evidence that the major destructive events in MS, as well as other non-central nervous system (CNS) autoimmune disorders, are much more than an immune attack on the CNS initiated by a misdirected immune system that attacks a “self ” antigen or antigens by a process called molecular mimicry. Extensive evidence suggests that inflammation, in turn, initiates excitotoxicity, which is responsible for the majority of pathological findings in all stages of the disease, especially a loss of oligodendroglia (source of myelin) and axon injury in MS. Excitotoxicity also is a better explanation for progressive MS, in which the immune attack has either slowed or is halted; yet, the destructive pathology continues to progress. It also explains the destructive lesions seen in gray matter, which is essentially devoid of inflammation. It has recently been shown that most of the damage to the oligodendrocytes, as well as axonal injury, is secondary to excitotoxicity. While there is a growing appreciation that excitotoxicity plays a major role, there has been little effort to link the immune changes to the excitotoxic process, recently named immunoexcitotoxicity, even though the role of excitotoxicity has been shown to occur in the inflammatory stage in the beginning and throughout the process of the disease, particularly the chronic progressive stage. It is also known that peripheral glutamate receptors exist throughout the body, thus making the process of immunoexcitotoxicity a possible integral part of all or most autoimmune disorders in which the immune system is intimately linked to enhancing the excitotoxic process. This is of special concern now that peripheral glutamate receptors have been isolated in many peripheral tissues and are known to be fully functional.
Staged and combined resection of a posterior fossa ganglioglioma
Authors: Rennert Robert C. , Fredrickson Vance L. , Mortimer Vance R. , Couldwell William T.
Published: January 2025

Background:

Posterior fossa gangliogliomas with extension into the cerebellopontine angle are extremely rare and can be challenging to resect because they are infiltrative and the regional neurovasculature is complex.[1,2] Tumor grade may best predict oncologic outcome.[1] Histologic grading can be used to balance surgical aggression with the risk of cranial neuropathies.

Case Description:

During an evaluation for headaches, a 19-year-old woman was found to have a 5.3 × 4.0 × 3.5-cm left lateral cerebellar and cerebellopontine angle tumor, with an apparent intrinsic origin and significant exophytic extension. The lesion was minimally enhancing and partially cystic and had significant calcifications. On examination, she was neurologically intact, with the exception of mildly decreased left oropharyngeal sensation. She underwent a left retrosigmoid craniotomy for tumor debulking and tissue diagnosis; the tumor was found to be adherent to cranial nerves 7 through 11. Pathological evaluation demonstrated a ganglioglioma (World Health Organization grade I). A safe maximal resection was recommended on multidisciplinary review. A secondary left far lateral craniotomy and C1 hemilaminectomy were performed, allowing for a complete resection of the residual tumor. The patient was discharged on postoperative day 6 at her neurologic baseline, with the exception of new mild left V2–3 paresthesias that were resolved by 6-month follow-up. Postoperative and 6-month magnetic resonance imaging demonstrated a gross total resection with no complications.

Conclusion:

For rare, low-grade tumors, a staged, histology-guided, safe maximal resection can maximize functional and oncologic outcomes.
Radiological and pathological findings of spinal intramedullary granular cell tumor
Authors: Inagaki Ryo , Kohno Daisuke , Shigekawa Seiji , Inoue Akihiro , Kitazawa Riko , Kunieda Takeharu
Published: January 2025

Background:

Granular cell tumors (GCTs) are rare, usually benign, tumors with classic histomorphology. This tumor can occur throughout the body, but the spine is a distinctly rare location. Here, we report a very rare case of intramedullary GCT arising in the thoracic spinal cord.

Case Description:

A 36-year-old woman presented to our hospital with an approximately 1-year history of gradually worsening numbness in the left toe and weakness in both lower limbs. Neuroimaging showed a tumor mass in the upper spine at the level of thoracic vertebrae 7-8, appearing hypointense on T2-weighted imaging (WI) and showing uniform gadolinium enhancement on T1-WI. Complete surgical resection was successfully performed. Histopathological examination revealed round or polygonal cells with abundant granular eosinophilic cytoplasm strongly staining for S-100 and SOX10, and benign intramedullary GCT in the thoracic spinal cord was diagnosed. Postoperative magnetic resonance imaging (MRI) showed no residual tumor, and the patient recovered well from this intervention, showing no sequelae. Follow-up neuroimaging after 2 years showed no signs of recurrence.

Conclusion:

This report describes an extremely rare case of GCT arising from the intramedullary thoracic spinal cord, which is difficult to diagnose by routine neuroimaging. Therefore, accurate diagnosis requires careful identification of clinical signs, MRI including hypointensity on T2-WI, and analysis of combined morphologic and immunohistochemical studies.
Русские старожилы арктических территорий Якутии: результаты и актуальные проблемы исследований
Authors: Алексеев А.Н.
Published: January 2025

В статье рассматриваются основные результаты исследований истории и культуры русских старожилов арктических территорий Якутии, предлагаются наиболее актуальные, с точки зрения автора, проблемы дальнейших исследований.

The article examines the main research results into the history and culture of Russian old-timers in the Arctic territories of Yakutia, and proposes the most pressing issues for further research from the author’s point of view.
Якутский отдел Императорского Православного Палестинского общества: по материалам газеты «Якутские епархиальные ведомости»
Authors: Юрганова И.И.
Published: January 2025

В исследовании на основе анализа публикаций епархиальной прессы дано представление о деятельности и приоритетах «самого дальнего и холодного» регионального отделения Императорского Православного Палестинского общества – Якутского отдела (1893‒1917), составленное с учетом немногочисленной историографии и источникового потенциала проблемы на основе материалов газеты «Якутские епархиальные ведомости». Обращение к епархиальной периодике предоставило возможности рассмотрения истории отдела на первом этапе его функционирования (1893–1905 гг.), обозначения основных направлений, состава и социальной структуры регионального отделения, выявления трудностей организационной работы, обусловленных как объективными особенностями проживания в северных условиях, так и субъективными факторами.

The study examines the activities of the Yakut Department, the first regional branch of the Imperial Orthodox Palestinian Society, which was reflected in the publications of the Yakut Diocesan Gazette newspaper. Two stages in the department’s activities have been identified based on newspaper publications. The first is associated with the names of Bishops Meletius (Yakimov) and Nikanor (Nadezhdin) and is characterized by the greatest activity (1893- 1905). Membership in the Yakut Department demonstrates a wide range of participants, including regional leadership and bureaucracy, representatives of the merchant class, clergy and non-native elites. The priorities of the regional office were determined, consisting in collecting donations and cultural and educational work (readings and conversations, including in the Yakut language), the circle of readings, their geography and organizers were identified, the use of modern technical means for this period was established. The second stage of the department’s activity is correlated with the change of both the spiritual and secular leadership of the region. It is obvious that the potential of the diocesan press gives grounds to identify the successes and difficulties of the organizational work of the Yakut Department of the Imperial Orthodox Palestinian Society, due to both objective reasons for living in northern conditions and subjective factors.
Отражение северного ландшафта и реалий быта в фольклорных произведениях русских старожилов Северо-Востока Якутии
Authors: Чарина О.И.
Published: January 2025

На основе русского фольклора старожилов арктической зоны Якутии рассмотрены особенности изменения текста на уровне слова. Материалом послужили эпические произведения фольклора, а также короткие песни, которые исполняли старожилы русских сел Северо-Востока Якутии, отраженные в записях конца XIX ‒ XX вв. Применены выборка лексем, сравнительно-сопоставительный анализ текстов, определенной лексики. Северный ландшафт, животный мир, жилище, одежда, пища представлены как русскими образами, так и некоторыми внедренными, взятыми из фольклора соседних народов, в основном якутов.

Based on the Russian folklore of old-timers of the Arctic zone of Yakutia, the features of changing the text at the word level are considered. Texts published in collections were used to clarify the specifics of showing local nature and everyday life: “Dictionary”, collected by V.G. Bogoraz [1901], “Folklore of the Russkoe Ustye” [1986], “Russian Epic Poetry of Siberia and the Far East” [1991]. The material was epic works of folklore, as well as short songs performed by old-timers of Russian villages in North-East of Yakutia, reflected in the records of the late 19th – 20th centuries. In quantitative terms, more than 350 texts of epics, historical songs, ballads, fairy tales, street’s songs, “andylshchyna” were reviewed. A comparative analysis of texts and certain vocabulary was used. The lexis showing the space of the Arctic world was considered: northern landscape, animal world, village, dwelling, food, household items. Old Russian dialect words such as “sendukha”, “ushkan”, “tėlno” are presented. Vocabulary taken from the folklore of neighboring peoples, mainly the Yakuts, is introduced: “yurt”, “khoton”, “oron”, “sora”, “kumys”.
Коллекция намогильных пирамидок – цаца из Саратовского областного музея краеведения как источник по изучению похоронно-погребальной практики у калмыков
Authors: Кольцов П.М. , Батыров В.В. , Умгаев С.А.
Published: January 2025

Статья посвящена анализу намогильных пирамидок, связанных с культурно-мировоззренческими ценностями калмыков и, в частности, с практикой обряда перехода. С середины XIX в. калмыки под влиянием внешних и внутренних факторов начинают переходить к захоронению покойных в земле, что привело к появлению первых кладбищ и обустройству намогильных сооружений – стул цаца, которые связаны с культом предков. Научная новизна заключается в том, что публикация малоизвестной коллекции намогильных пирамидок позволяет в значительной степени расширить источниковую базу для дальнейшего изучения традиционной похоронно-погребальной обрядности калмыков.

The article is devoted to the analysis of tomb pyramids associated with the cultural and ideological values of the Kalmyk in general and the practice of the rite of passage in particular. The purpose of this article is to introduce into scientific circulation the tomb pyramids from the collection of Saratov Regional Museum of Local History, which significantly complement the knowledge about the traditional rituals of the Kalmyk. The objectives of the study include the description and analysis of the tomb pyramids. The methodological basis of this article is the principles of historicism, system analysis and an objective approach to the subjects studied. The following methods were used in the study: descriptive, typological, historical-comparative and analytical. Under the influence of external and internal factors, the Kalmyk began to move to burying the dead in the ground, which led to the appearance of the first cemeteries and the construction of tomb in the form of pyramids, which are associated with the cult of ancestors. The publication of a unique collection of tomb pyramids allows us to significantly expand the source base for further study of traditional funeral rites of the Kalmyk.
Чатские билабиальные согласные по акустическим данным
Authors: Якимец Н.В.
Published: January 2025

Впервые методами акустического и аудитивного анализа были исследованы билабиальные согласные звукотипы «p», «b», «m» и «w» в языке чатских татар. Были изучены артикуляционно-акустические характеристики согласных, взаимосвязь между этими характеристиками и позиционно-комбинаторными условиями, в которых данные согласные встречаются. Для этого были проанализированы осциллограммы и спектрограммы согласных; измерены частоты основных тонов, второй форманты, интенсивность и длительность; оценена напряженность артикуляции. На основании полученных данных были описаны некоторые артикуляционные характеристики согласных. Результаты показывают зависимость характеристик «p», «b» и «m» от палатальной гармонии гласных в слове.

Acoustic and auditive analyses were used for the first time to study bilabial consonant sounds of types “p”, “b”, “m”, and “w” in the language of Chat Tatars. This research aimed to study the acoustic and articulatory properties of the consonants and to establish a relationship between these properties and the positional and combinatorial conditions in which the consonants occur. To do this, recordings of 69 words containing these sounds from 5 native speakers were annotated using Speech Analyzer 3.1.2.0. The waveforms and spectrograms of the consonants were examined; pitch, formants (F2), intensity, and duration were measured; tenseness of articulation was evaluated. Based on these data some articulatory properties were described. The results show that the acoustic and articulatory properties of “p”, “b”, and “m” depend on the palatal vowel harmony in the word. The consonant “w” does not show such dependence. The average intensities of the consonants differ by about 10 dB. The average pitch values for “b”, “m”, and “w” sound types are comparable, indicating that the position of the larynx does not differ during their articulation.
Применение алгоритмов элитарной муравьиной системы и Max-Min муравьиной системы для оптимизации маршрутов в сетях квантового распределения ключей
Authors: Раздьяконов Е.С. , Корчагин С.А. , Тимошенко А.В. , Булатов М.Ф.
Published: January 2025

Данное исследование посвящено оптимизации маршрутов в сетях квантового распределения ключей (КРК), особенностями которых является ряд физических ограничений и сильная зависимость от топологии. В работе рассматривается применение двух вариаций алгоритма муравьиных колоний, алгоритмов элитарной муравьиной системы (EAS) и Max-Min муравьиной системы (MMAS), для построения оптимальных маршрутов в сетях КРК. Была представлена метрика коммуникационной эффективности маршрута сети КРК, позволяющая оценивать качество маршрута в соответствии с заданными требованиями к пропускной способности и безопасности. Особенностью данной метрики является ее неаддитивная составляющая пропускной способности, зависящая от минимальной эффективности соединения в маршруте. Была проведена серия экспериментов на случайно сгенерированном планарном графе для длинных и коротких маршрутов с алгоритмами EAS и MMAS, в результате которых MMAS оказался значительно более эффективным для длинных маршрутов, но в случае коротких маршрутов EAS находил маршрут быстрее без значительной потери в качестве решения. Результаты, полученные в данном исследовании, могут быть применены в решении задач динамической маршрутизации, а также оптимизации топологии сетей квантового распределения ключей.

This study focuses on route optimization in quantum key distribution (QKD) networks, whose features are a number of physical constraints and strong topology dependence. This paper examines the application of two variations of the ant colony algorithm, the elitist ant system (EAS) and Max-Min ant system (MMAS) algorithms, to construct optimal routes in QKD networks. A metric for the communication efficiency of a route in QKD networks has been presented to evaluate the quality of a route according to given capacity and security requirements. The peculiarity of this metric is its non-additive capacity component, which depends on the minimum link efficiency in the route. A series of experiments were conducted on a randomly generated planar graph for long and short routes with EAS and MMAS algorithms, which resulted in MMAS being significantly more efficient for long routes, but in the case of short routes, EAS found the route faster without significant loss in solution quality. The results obtained in this study can be applied in solving problems of dynamic routing, as well as optimization of the topology of quantum key distribution networks.
Mononuclear Palladium(I) and Palladium(III) Coordination Compounds
Authors: Banerjee Siddhartha , Chakrabarti Sagnik , Bouley Bailey , Wahlmeier Amy , Mirica Liviu
Published: January 2025

Palladium coordination complexes are invaluable catalysts in organometallic reactions, facilitating a plethora of synthetically useful organic transformations that include C-H functionalization and C-C/C-heteroatom bond formation reactions. The proposed mechanisms for such reactions usually invoke two-electron pathways involving diamagnetic Pd0, PdII, and PdIV intermediates. However, recent research has focused on the viability of paramagnetic Pd species with +1 and +3 oxidation states as plausible intermediates. The past two decades have seen a renewed interest in the isolation and characterization of such transient species to obtain a better understanding of their structure and reactivity. This review focuses on the coordination chemistry of mononuclear PdI and PdIII compounds that have been isolated and characterized using spectroscopic techniques such as electron paramagnetic resonance (EPR), nuclear magnetic resonance (NMR), cyclic voltammetry (CV), electrospray ionization mass spectrometry (ESI-MS), single crystal X-ray crystallography (SC-XRD), and X-ray absorption spectroscopy (XAS) methods. It is expected that the knowledge gained from studying the electronic structure and spectroscopic properties of these compounds will be used to facilitate new modes of reactivity inaccessible to traditional Pd0/II/IV chemistry.
Investigation of Arenes and Heteroarenes Nitration supported by High-Throughput Experimentation and Machine Learning
Authors: Kerackian Taline , Daniel Matthieu , Wespiser Clément , Pasquinet Eric , Romero Eugénie
Published: January 2025

Access to the nitro functional group is a very common and longstanding transformation of interest in many fields of chemistry. However, the robustness and specificity of this transformation can remain challenging, particularly in the case of heteroarene nitration. From this observation, a large investigation was initiated to screen nitration conditions on various arenes and heteroarenes. The systematical and diverse study of both nitrating agents and activating reagents was conducted using high-throughput experimentation, to afford high quantity and high quality data generation. General trends have been identified and correlated to the electronic property of the heteroarene, notably the difficult nitration of electron-poor heteroarenes was highlighted. Original combinations of reagents were found to perform well in nitration reactions. The obtained data were also used to design a predictive tool relying on machine learning in order to provide the best nitration reaction conditions depending on the targeted substrate. The limited predictive efficiency obtained pointed out the importance of the diversification and the chemically relevant encoding of the data set.
Nature-Inspired C-terminus Modification of Oligo-prolines to Stabilize PPII Helix
Authors: Das Paramesh , Ghosh Amar , Baruah Kalpita , Borah Debashree , Sarma Bani
Published: January 2025

Oligomers of proline (oligo-Pro) are valuable models for studying the structural and thermodynamic properties of the all-trans polyproline II (PPII) helix. These peptides, in their rigid PPII form, serve as spectroscopic and molecular rulers. However, proline cis/trans isomerization can lead to the undesired all-cis PPI conformation in nonpolar solvents. In this study, we investigated mechanisms to stabilize the PPII structure by analyzing PPII regions in the Protein Data Bank (PDB) and observed a high prevalence of α-helices and β-turns at the C-termini of PPII helices. These motifs likely contribute to PPII stabilization through CO∙∙∙HN hydrogen bonding with the C-terminal carbonyl. To probe this, we synthesized oligo-Pro peptides of varying lengths, each capped with C-terminal β-turns. These peptides exhibited enhanced PPII stability, even in solvents that typically favor PPI. Our findings suggest that C-terminal hydrogen bonding promotes CO∙∙∙CO n → π* interactions within the peptide chain, playing a key role in stabilizing the PPII helix. These insights offer new strategies for designing stable PPII peptides and understanding the underlying mechanisms of PPII stabilization.
Novel pseudomomentum-translational sum rule for the molecular Berry curvature
Authors: Steinmetz Dominik , Pausch Ansgar
Published: January 2025

The molecular Berry curvature plays an important role for electronic structure calculations within the adiabatic Born– Oppenheimer approximation and is connected to many magnetic phenomena such as the Aharanov–Bohm and the chirality-induced spin selectivity (CISS) effect. For molecules in external magnetic fields, the Berry curvature is essential to achieve a qualitatively correct description of nuclear motion. Here, it is responsible for screening the Lorentz forces acting on moving nuclear charges. This connection has recently been exploited to derive a new type of population analysis known as Berry charges. In this work, we derive a novel sum rule for the molecular Berry curvature. This pseudomomentum-translational sum rule is then used to reveal the connection between Berry charges and the well-known generalized atomic polar tensor (GAPT) charges. Furthermore, we present an efficient integral-direct implementation of the molecular Berry curvature for molecules in finite magnetic fields into the TURBOMOLE program suite. This is used to further demonstrate the connection between Berry and GAPT charges for a variety of larger molecules, comparing the results to other established types of partial charges.
Usage of Unsupported Technologies in Websites Worldwide
Authors: Nugroho Pascal Alfadian , Putra Raymond Chandra , Maulana Rajasa Cikal , Tandra Vinson
Published: January 2025

Websites using unsupported 3rd party technologies (libraries, frameworks, plugins, etc) are generally not recommended, especially due to security issues that are left unfixed. However, upgrading to supported technologies is also challenging, hence not all web maintainers upgrade their technology dependencies. Measuring the existence of unsupported technologies in the wild may contribute to the sense of urgency in keeping technologies updated. Our research proposed a method to measure the existence of unsupported technologies in international websites, using HTTP Archive as the data source. The contribution from our research is the method as well as the snapshot result from January 2023 data. The method is composed of four steps, namely: identify the list of websites, identify technologies used, group by technology names and retrieve currently supported versions, and compare versions between usage and supported versions. From the January 2023 data, we found several interesting results. One is that the higher the website rank is, the higher the number of supported technologies used. Another finding was that worldwide websites also generally use more supported versions of technologies, compared to Indonesian websites. Further research may be performed for longitudinal analysis of technology support evolution.
Dual Mode MIMO-Beamforming Four Elements Array Antenna for Mobile Robot Communications at 5.6 GHz
Authors: Muhsin Muhsin , Saharani Aulia , Nurlaili Afina Lina
Published: January 2025

Mobile robot communications are essential for robot teamwork. To enable communication between robots, reliable wireless communications must be deployed. Higher performance and capacity of communication are required. Multiple-input multiple-output (MIMO) and beamforming are important wireless communication technologies that use multiple antennas to improve communications performance and capacity. However, these two technologies have different requirements. MIMO requires the antenna element to be independent. While beamforming needs antennas to be coupled and fed by the same source. This paper proposes a dual-mode antenna for mobile robot communications at 5.6 GHz that supports both beamforming and MIMO. A single antenna consists of a planar dipole antenna arranged in a circular configuration. This antenna is then expanded to a four-element array antenna. Both MIMO and beamforming evaluations are performed. In MIMO mode, the BER performance is very similar to a non-correlated MIMO antenna. It is supported by the very low correlation between antennas below 0.01. Low coupling is also achieved below -16.5 dB. In beamforming mode, the proposed antenna achieves more than 8.6 dBi gain and good beam steering capability. It is supported by beam suppression with a 90° phase difference between the front and back direction. The proposed antenna performs well in both the MIMO and beamforming modes.
Energy Saving Analysis on Distribution Network with Incorporation of D-STATCOM Using Firefly Algorithm and Power Loss Index
Authors: Olabode Olakunle Elijah , Ajewole Titus Oluwasuji , Ariyo Funso Kehinde
Published: January 2025

This present work investigated the effects of reactive power compensation with the use of a Distribution Static Synchronous Compensator (D-STATCOM) on a practical distribution network. In the approach proposed, the network steady-state parameters were obtained with a backward forward sweep power flow technique, the possible sites for D-STATCOM were predetermined with power loss index while the firefly algorithm was employed for determining the optimal sizes and sites respectively. Three different levels of D-STATCOM penetrations were investigated and their effects on voltage profile enhancement, active power loss reduction, cost of energy savings, payback times, and cost of procurement were assessed. The best optimal sites and sizes obtained after several simulations for case I, case II, and case III are (6, 1000kVar); (12, 349.69kVar; 22, 867.29kVar) and (5, 1200kVar; 14, 424.34kVar; 21, 350kVar) respectively. Also, the percentage improvements at the bus with minimum voltage magnitude for cases I to III are 0.6, 0.78, and 0.79% while the accompanied active power loss reductions are 59.03, 70.57 and 91.78 %. From the economic perspective, the cost of procurement ($), annual energy savings ($), and the payback time (years) for the three cases examined are (5,303.5, 1,461.00, 3.63); (6,454.25, 1,746.66, 3.69); (10,471, 2, 271.58, 4.61) respectively. Also, results validation showed that the approach proposed outsmarts particle swarm optimization and network feeder reconfiguration. The outcome of this work findings application in performance enhancement of real-life distribution networks.
GAMA CUTE: Development of a Web-based for Gadjah Mada Caring University for Thalassemia Exit Prediction Tool by Applying Machine Learning
Authors: Saputra Dimas Chaerul Ekty , Afiahayati Afiahayati , Ratnaningsih Tri
Published: January 2025

Blood disorders occur in one or several parts of the blood that affect the nature and function, and blood disorders can be acute or chronic. Blood disease consists of several types, such as anemia. Anemia is the most common hematologic disorder associated with a decrease in the number of red blood cells or hemoglobin, causing a decrease in the ability of the blood to carry oxygen throughout the body. Patients with anemia in Indonesia have increased for the age of 15-24 years. This study aimed to conduct a screening test for anemia using machine learning. It is expected to know the process of knowing the type of anemia suffered. The machine learning technique used to identify the cause of anemia is divided into four classes, namely Beta Thalassemia Trait, Iron Deficiency Anemia, Hemoglobin E, and Combination (Beta Thalassemia Trait and Iron Deficiency Anemia or Hemoglobin E and Iron Deficiency Anemia). This study would apply the K-Nearest Neighbor (KNN) and Random Forest (RF) methods to build a model on the data collected. The evaluation results using a confusion matrix in the form of accuracy, precision, recall, and f1-score against the KNN and RF methods are 79.36%, 59.40%, 62.80%, and 62.80%. In comparison, the RF is 87.30%, 90.89%, 78.40%, and 81.00%. From the results of comparing the two methods, the Graphic User Interface (GUI) implementation using python applies the RF method. The classifier that gets the highest value among all these parameters is called the best machine learning algorithm to perform screening tests for anemia.
The Effectiveness of Data Imputations on Myocardial Infarction Complication Classification Using Machine Learning Approach with Hyperparameter Tuning
Authors: Mazdadi Muhammad Itqan , Saragih Triando Hamonangan , Budiman Irwan , Farmadi Andi , Tajali Ahmad
Published: January 2025

Complications from Myocardial Infarction (MI) represent a critical medical emergency caused by the blockage of blood flow to the heart muscle, primarily due to a blood clot in a coronary artery narrowed by atherosclerotic plaque. Diagnosing MI involves physical examination, electrocardiogram (ECG) evaluation, blood sample analysis for specific heart enzyme levels, and imaging techniques such as coronary angiography. Proactively predicting acute myocardial complications can mitigate adverse outcomes, and this study focuses on early prediction using classification methods. Machine learning algorithms such as Support Vector Machine (SVM), Random Forest, and XGBoost were employed to classify patient medical records accurately. Techniques like K-Nearest Neighbors (KNN) imputation, Iterative imputation, and Miss Forest were used to handle incomplete datasets, preserving vital information. Hyperparameter optimization, crucial for model performance, was performed using Bayesian Optimization, which minimizes the objective function by modeling past evaluations. The contribution to this study is to see how much influence data imputation has on classification using machine learning methods on missing data and to see how much influence the optimization method has when performing hyperparameter tuning. Results demonstrated that the Iterative Imputation method yielded excellent performance with SVM and XGBoost algorithms. SVM achieved 100% accuracy, precision, sensitivity, F1 score, and AUC. XGBoost reached 99.4% accuracy, 100% precision, 79.6% sensitivity, an F1 score of 88.7%, and an AUC of 0.898. KNN Imputation with SVM showed results similar to Iterative Imputation with SVM, while Random Forest exhibited poor classification outcomes due to data imbalance, causing overfitting.
Optimizing Disaster Response: A Systematic Review of Time-Dependent Cumulative Vehicle Routing in Humanitarian Logistics
Authors: Hartama Dedy , Wanayumini Wanayumini , Damanik Irfan Sudahri
Published: January 2025

Effective delivery of aid during disasters is crucial for mitigating impacts and ensuring well-being. A major challenge in humanitarian logistics is optimizing vehicle routing to maximize efficiency and minimize delivery times. which included 50 studies published between 2012 and 2022. We used the prism method to guide the process of choosing a study, which started from 200 Abstract which is identified and ends with 50 appropriate studies for in -depth analysis. This systematic literature review (SLR) examines the Time-Dependent Cumulative Vehicle Routing Problem (TDCVRP) in humanitarian logistics, identifying VRP variants, their applications, and effectiveness in disaster scenarios. Using a comprehensive search and PRISMA guidelines, the review highlights the importance of optimization models and advanced algorithms. Applications include aid delivery, evacuation management, and facility location optimization, though challenges like computational complexity and reliance on real-time data persist. The review identifies research gaps and suggests future research should focus on integrating advanced methods and improving practical applicability in disaster responses.
Optimization of YOLOv4-Tiny Algorithm for Vehicle Detection and Vehicle Count Detection Embedded System
Authors: Muwardi Rachmat , Nugroho Ivan Prasetyo , Salamah Ketty Siti , Yunita Mirna , Rahmatullah Rizky , Chung Gregorius Justin
Published: January 2025

Currently, the implementation of object detection systems in the traffic sector is minimal. CCTV cameras on highways and toll roads are primarily used to monitor traffic conditions and document violations. However, the data recorded by these cameras can be further utilized to enhance traffic management systems. The author proposes a vehicle detection and counting system using YOLOv4-Tiny. The research aims to improve vehicle detection and counting accuracy by employing a median filter and grayscale processing, which simplify object detection. The proposed YOLOv4-Tiny algorithm has shown impressive results on various datasets, including MAVD, GRAM-RTM, and author dataset. The system achieved a detection accuracy of 98.95% on the MAVD dataset, 99.5% on the GRAM-RTM dataset (comparable to YOLOv4), and 99.1% on the author dataset. Furthermore, the system operates at 25 frames per second (FPS), a notably high rate compared to other methods. While the system demonstrates excellent accuracy in counting cars, it encounters some accuracy loss with other vehicle classifications. The author concludes that the system is highly suitable for real-world applications but notes that inaccurate labeling can lead to vehicle counting errors.
Visible Light Communication System Design Using Raspberry Pi4B, LED Array, and MQTT Synchronization Protocol
Authors: Rafi Akbar Teuku Alif , Catur Apriono
Published: January 2025

Visible light communication emerged as the solution to overcome limitations exist in RF-based communication system. Although many research has been done on VLC, there are still a lot room for improvements, especially in the design of the VLC itself. This study discusses a simple visible light communication system design that transmits temperature and humidity information. The system uses Array 2×2 LED configuration to transmit data and photodiode to receive the optical signal. Raspberry Pi is used as the signal processor. The research carried out variations in the color of LED used, variations in the method of synchronization, and variations in the data rate transmission with BER value as the main parameter to be analyzed. The research contribution is to propose a simple visible light communication design that transmit and receive information in reference to room temperature and humidity using Raspberry Pi and DHT-11 sensor, while also implementing two synchronization methods to maximize synchronization in transmission thus minimizing the BER value in higher bit rate. The LED used is blue with an average voltage of 0.0423 V for bit ‘1’ and 0.00448 V for bit ‘0’. The throughput can be achieved are within range 1bps to 10 kbps with BER 0.5 as a threshold. The implementation of the synchronization method decreases the average BER value by 0.0945 with the implementation of transmission calibration synchronization and decreases the average BER value by 0.1221 using the MQTT communication protocol. In conclusion, the design has limitations through the component used in the transmitting and receiving end with BER values relatively high. Further research for system development can be done by implementing Forward Error Correction to minimize errors that occur in the transmission and collaborating with vendors with same research field for the latest components for VLC system design.
The Combination of C4.5 with Particle Swarm Optimization in Classification of Class for Mental Retardation Students
Authors: Nova Sausan Hidayah , Warsito Budi , Widodo Aris Puji
Published: January 2025

Mental retardation or brain weakness is a condition of children who experience mental disorders. There are several characteristics to know the child has mental retardation. When entering a school, teachers are expected to be able to determine the right class for mental retardation students according to their category. Data mining is the process of finding patterns in selected data using artificial intelligence and machine learning. Algorithm C4.5 is one of the classification techniques in data mining. C4.5 can be used to create decision trees and classify data that has numeric, continuous, and categorical attributes. But C4.5 has the disadvantage of reading large amounts of data and cannot rank every alternative. PSO is an optimization algorithm for feature selection that can improve performance in data classification. Therefore, this study proposes an algorithm that can overcome the weaknesses of C4.5 by combining PSO. This study aims to classify a class of new mental retardation students using a combination of C4.5 as a classification and PSO as a feature selection to determine the attributes that affect the level of accuracy. The contribution of this research is to make it easier for the school to determine the new class of mental retardation students so that it is appropriate and according to their needs. The classification process in this study uses a combination of C4.5 and PSO. The validation used in this model is 10-fold cross-validation, and the evaluation uses a confusion matrix. This study resulted in an accuracy of C4.5 before using PSO of 91%. While the accuracy of C4.5 uses a PSO of 93%. Of the 20 attributes, there are 6 attributes that affect the level of accuracy. This study shows that PSO can be used to implement feature selection and increase the accuracy value of C4.5 by 2%.
Development of Novel Machine Learning to Optimize the Solubility of Azathioprine as Anticancer Drug in Supercritical Carbon Dioxide
Authors: Waskita Arya Adhyaksa , Bissa Stevry Yushady CH , Satya Ika Atman , Alwi Ratna Surya
Published: January 2025

Supercritical carbon dioxide (Sc-CO2) has thus been proposed as an appropriate solvent for diluting the pharmaceuticals to increase particle size. The use of supercritical fluids (SCFs) in various industrial applications, such as extraction, chromatography, and particle engineering, has attracted considerable interest. Recognizing the solubility behavior of various drugs is an essential step in the pharmaceutical industry's pursuit of the most effective supercritical approach. In this work, four models were used to predict the solubility of Azathioprine in supercritical carbon dioxide, including Ridge regression (RR), Huber regression (HR), Random forest (RF), and Gaussian process regression (GPR). The R-squared scores of all four models are 0.974, 0.6518, 0.966, and 1.0 for Ridge regression (RR), Huber regression (HR), Random forest (RF), and Gaussian process regression (GPR) models, respectively. The RMSE error rates of 2.843 ×10-13, 7.036 ×10-12, 5.673 ×10-13, and 1.054 ×10-30 for the RR, HR, RF, and GPR models, respectively. MAE metrics of 1.205 ×10-6, 2.151  ×10-6, 5.997 ×10-7 and 9.419 ×10-16 errors were also found in the RR, HR, RF, and GPR models, respectively. It was found that Ridge regression (RR), Random forest (RF), and Gaussian process regression (GPR) models can be used to predict any compound's solubility in supercritical carbon dioxide.
Palm Print Recognition Using Intelligent Techniques: A review
Authors: Al-Taie Sara A. Mohammed , Khaleel Baydaa I.
Published: January 2025

Hand or Palm print recognition systems are one of the efficient people recognition and authentication systems that provide high-security levels by approving the entering and exiting of people such as employees in the work field or companies. The basis for using palmprints lies in the fact that no two individuals have exactly the same palmprint pattern, moreover palmprints remain more or less stablethroughout the lifetime and are easily obtainable using standard imaging techniques. Palm print recognition systems process picture data from a photograph of a person's palm and compare it to a record for that person using a scanning device or camera-based application. There are numerous ways to obtain a palmprint image, including digital scanners. Researchers have taken palmprint photographs using video cameras, CCD-based scanners, and tripods. A CCD-based scanner may be used to take a high resolution image of a palmprint. A palm image can also be perfectly aligned with the user's hand thanks to the pegs on the CCD-based scanner The palmprint has a variety of natural ompositions that are rich in identifying characteristics like wrinkles, ridges, major lines, single, and minute points. Because of these, a palmprint is a distinctive biometric that is trustworthy for identifying humans As Artificial Intelligence (AI) methods and applications improved, the improvement of computer techniques and the usage of  techniques increased in all fields including people recognition field. Many intelligent techniques are used to recognize people such as neural networks, the Genetic Algorithm, Particle Swarm Algorithm, and Deep Learning all these techniques are used and have almost the same recognition accuracy
Social Media Sentiment Analysis Using Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU)
Authors: Adam Ahmad Zahri Ruhban , Setiawan Erwin Budi
Published: January 2025

The advancing technologies are aimed to maximize human performance. One of the great developments in technology is social media. The social media used in this study is Twitter because most people in Indonesia give their opinions to the public through tweets. The opinions given are very diverse, where they write positive, negative, and neutral opinions. The purpose of this study is to analyze the sentiments of the opinions given by the public in Bahasa Indonesia. To conduct sentiment analysis, tweets are collected by crawling the data. Tweets are then labeled positive, negative, and neutral and then represented as 1, -1, and 0. The method used to classify tweet sentiment is the Convolutional Neural Network (CNN) and Gated Recurrent Unit method (GRU). Research stages including feature selection, feature expansion, preprocessing and balancing with SMOTE. The highest accuracy value obtained on the CNN-GRU model with an accuracy value of 97.58% value. Based on these tests, it can be concluded that sentiment analysis research on Twitter social media using the Convolutional Neural Network and Gated Recurrent Unit methods can produce fairly high accuracy, and feature expansion testing of the deep learning model can provide a significant increase in accuracy values.
Classification and Clustering of Internet Quota Sales Data Using C4.5 Algorithm and K-Means
Authors: Astuti Eriska Vivian , Afandi Asep , Effendi Dwi Marissa
Published: January 2025

The number of restrictions or limits on internet use is known as internet quota. When you use internet data for a short time, you usually run out of bandwidth. In the Candimas South Abung area, many quotas have been sold in various variants. Visitors to quota outlets have access to various kinds of quota references that they can buy. Apart from guaranteeing the quality of the quotas sold, sales always increase every year, especially in the various quota variants. Based on quota data for 2019 to 2022. This study aims to analyze internet quota sales statistics in the Candimas area between 2019 and 2022. In 2021-2022 the classification produces an accuracy of up to 100% where the best-selling data dominates while clustering remains at the same figure, namely 19 data are very salable, 43 data are lacking sold, and 178 data did not sell. We use the C4.5 classification algorithm and K-Means clustering to identify patterns in the data and provide insight into which brand quotas are the most popular. Our findings can help Xena Cell counter owners make informed decisions about which quota to add or remove to optimize sales and minimize losses.