bluuebunny/crossref_metadata_2025 huggingface dataset:
Enabling Energy-Efficient and Low-Latency of Sparse Matrix-Vector Multiplication on GPUs
Authors: Ashoury Mina , Loni Mohammad , Khunjush Farshad , Daneshtalab Masoud
Published: November 2023

Sparse matrix-vector multiplication (SpMV) is an essential linear algebra operation that dominates the computing cost in many scientific applications. Due to providing massive parallelism and high memory bandwidth, GPUs are commonly used to accelerate SpMV kernels. Prior studies mainly focused on reducing the latency consumption of SpMV kernels on GPU by tackling the irregular nature of sparse matrices. However, limited attempts have been made to improve the energy efficiency (MFLOPS/Watt) of SpMV kernels, resulting in GPUs being excluded from the range of low-power scientific applications. Furthermore, prior work has primarily focused on optimizing the sparse matrix storage format; the literature ignores evaluating the impact of tweaking compilation parameters (e.g., \texttt{maxrregcount}, thread block size, and such). Lastly, little attention has been paid to preparing a comprehensive training dataset of running SpMV kernels and tweaking the hyperparameters of machine learning-based storage format predictors. To address these limitations, we present a novel learning-based framework, dubbed Auto-SpMV, that enables energy-efficient and low-latency SpMV kernels on GPUs. To achieve the best run time performance, Auto-SpMV proposes two optimization modes: \textit{compile-time} and \textit{run-time}. In the \textit{compile-time} mode, Auto-SpMV tweaks the compilation parameters according to the optimization objective, either lower latency or energy consumption. On the other hand, in the \textit{run-time} mode, Auto-SpMV selects the best sparse format for the input matrix based on an optimized machine learning model. To achieve the best classification results, 1) we collect the largest ever dataset by selecting different sparse matrices running with more than 15K configurations, and 2) we boost classification models by automatically tweaking the learning hyperparameters. Experimental results reveal that Auto-SpMV optimizes latency, energy consumption, average power, and energy efficiency in the \textit{compile-time} mode by up to 51.9%, 52%, 33.2%, and 53%, respectively, compared to the default setting. Auto-SpMV optimizes average power and energy efficiency in the \textit{run-time} mode by up to 34.6% and 99.7%, respectively, compared to the default setting. Finally, our experimental results show that Auto-SpMV generalizes to unseen matrices and hardware devices.
Measures of fragmentation of rest activity patterns: mathematical properties and interpretability based on accelerometer real life data
Authors: Danilevicz Ian Meneghel , Hees Vincent Theodoor van , Heide Frank van der , Jacob Louis , Landré Benjamin , Benadjaoud Mohamed Amine , Sabia Séverine
Published: November 2023

Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probability (TP), and self-similarity parameter (named α). However, their use remains mainly empirical. Therefore, we investigated the mathematical properties and interpretability of rest-activity fragmentation metrics by providing mathematical proofs for the ranges of IS and IV, proposing maximum likelihood and Bayesian estimators for TP, introducing the activity balance index metric, an adaptation of α, and describing distributions of these metrics in real-life setting. Analysis of accelerometer data from 2,859 individuals (age=60-83 years, 21.1% women) from the Whitehall II cohort (UK) shows modest correlations between the metrics, except for ABI and α. Sociodemographic (age, sex, education, employment status) and clinical (body mass index (BMI), and number of morbidities) factors were associated with these metrics, with differences observed according to metrics. For example, a difference of 5 units in BMI was associated with all metrics (differences ranging between -0.261 (95% CI -0.302, -0.220) to 0.228 (0.18, 0.268) for standardised TP rest to activity during the awake period and TP activity to rest during the awake period, respectively). These results reinforce the value of these rest-activity fragmentation metrics in epidemiological and clinical studies to examine their role for health. This paper expands on a set of methods that have previously demonstrated empirical value, improves the theoretical foundation for these methods, and evaluates their empirical worth in a large dataset.
The Simons Observatory: Large-Scale Characterization of 90/150 GHz TES Detector Modules
Authors: Dutcher Daniel , Duff Shannon M. , Groh John C. , Healy Erin , Hubmayr Johannes , Johnson Bradley R. , Jones Dante , Keller Ben , Lin Lawrence T. , Link Michael J. , Lucas Tammy J. , Morgan Samuel , Seino Yudai , Sonka Rita F. , Staggs Suzanne T. , Wang Yuhan , Zheng Kaiwen
Published: November 2023

The Simons Observatory (SO) is a cosmic microwave background instrumentation suite being deployed in the Atacama Desert in northern Chile.The telescopes within SO use three types of dichroic transition-edge sensor (TES) detector arrays, with the 90 and 150 GHz Mid-Frequency (MF) arrays containing 65% of the approximately 68,000 detectors in the first phase of SO.All of the 26 required MF detector arrays have now been fabricated, packaged into detector modules, and tested in laboratory cryostats.Across all modules, we find an average operable detector yield of 84% and median saturation powers of (2.8, 8.0) pW with interquartile ranges of (1, 2) pW at (90, 150) GHz, respectively, falling within their targeted ranges.We measure TES normal resistances and superconducting transition temperatures on each detector wafer to be uniform within 3%, with overall central values of 165 mK and 7.5 m\(\Omega\), respectively.Results on time constants, optical efficiency, and noise performance are also presented and are consistent with achieving instrument sensitivity forecasts.
What Role for ‘Generational Wealth’ in Explaining Racial Wealth Disparities?
Authors: Sabelhaus John , Thompson Jeffre
Published: November 2023

In light of a recent surge of interest in the topic of “generational wealth” and its potential to close racial disparities in wealth, this paper revisits an older literature with updated data and methods. Previous research found that inherited wealth contributed only modestly to racial disparities in wealth, or even reduced those disparities, but suffered from numerous shortcomings. This paper uses more recent data (through 2019) that recovers intergenerational transfers not reflected in prior research. We also include the asset value of defined benefit pensions – a source that accounts for 15 percent of all household wealth and is of particular importance for non-white households – into our measure of wealth, and exploit nonparametric decomposition techniques. Despite these innovations, our findings are consistent with earlier research that intergenerational transfers can account for a relatively small share of the racial disparities in wealth that we observe in the data. When no other controls are included, we find that differences in intergenerational transfers account for 13 to 16 percent of white/non-white private wealth gaps. When we control for lifetime earnings, workplace pensions, and a handful of additional human capital variables, the marginal contribution of intergenerational transfers shrinks considerably, but the combined portion of the racial wealth gap that is explained rises to 80 to 90 percent. Policymakers interested in helping households build wealth are advised to look to ways that would enable them to boost the earnings that they receive over their lifetime.
Impedance matching between SQUID and warm amplifier for TES readout in TDM
Authors: Gonzalez Manuel , Parot Yann , Prele Damien , Kirsch Christian , Cucchetti Edoardo , Peille Philippe , Murat David , Ravera Laurent , Kuur Jan
Published: November 2023

Current cryogenic instruments require an increasingly high number of super-conducting detectors. Large multiplexing factors are thus needed, increasing the bandwidth of the readout signals. In the specific case of transition edge sensors(TES), a cold amplification stage using superconducting quantum interference devices (SQUIDs) is usually coupled to a room temperature low noise amplifier (LNA). A resistive harness up to a few meters long connects these two stages, carrying signals with bandwidth of up to a few tens of MHz. In this context, it is reasonable to consider the possibility of impedance matching at the input of the LNA. In this paper we present the impact of such impedance matching for an ATHENA X-IFU like instrument.
Biomagnetism: Insights Into Magnetic Minerals Produced by Microorganisms
Authors: Byrne James M. , Amor Matthieu
Published: November 2023

Biomagnetism describes the biological origin of magnetism within living organisms. This phenomenon occurs due to the formation of iron-based minerals that exhibit magnetic ordering at room temperature. Perhaps the most studied form of biomagnetism originates in bacteria, especially magnetotactic bacteria that produce internal magnetite and greigite grains and iron-reducing bacteria that produce magnetite nanoparticles externally as a byproduct of iron respiration. These bacteria likely contribute to a significant proportion of environmental magnetite. The emergence of biomagnetism remains unclear, although it is thought that magnetotactic bacteria evolved this mechanism several billion years ago. Understanding how and why micro-organisms generate biomagnetism is helping to shed light on the origin of life on Earth and potentially on other planets. Biomagnetism is also of broad interest to industrial and environmental applications.
Magnetofossils: Relicts and Records of Deep Time and Space
Authors: Slotznick Sarah P. , Egli Ramon , Lascu Ioan
Published: November 2023

Magnetofossils are magnetic nanoparticles that represent the fossil remains of microorganisms that biomineralize magnetic minerals in a genetically controlled manner. Most magnetofossils found in the geologic record are produced by magnetotactic bacteria, which use them for navigating within their living environment. Magnetofossils can be identified using a combination of magnetic and imaging techniques. A common attribute of magnetofossils, although not pervasive, is that they are arranged in chains, which determines their specific magnetic properties. Magnetofossil signatures have been reported from ancient rocks to modern sediments and even in extraterrestrial materials. They provide a window into biomineralization, past environments, and ancient magnetic fields, as well as supplying fuel for questions on the origin of life in the Solar System.
Snowmass2021 cosmic frontier white paper: Ultraheavy particle dark matter
Authors: Carney Daniel , Raj Nirmal , Bai Yang , Berger Joshua , Blanco Carlos , Bramante Joseph , Cappiello Christopher , Dutra Maíra , Ebadi Reza , Engel Kristi , Kolb Edward , Harding J. Patrick , Kumar Jason , Krnjaic Gordan , Lang Rafael F. , Leane Rebecca K. , Lehmann Benjamin V. , Li Shengchao , Long Andrew J. , Mohlabeng Gopolang , Olcina Ibles , Pueschel Elisa , Rodd Nicholas L. , Rott Carsten , Sengupta Dipan , Shakya Bibhushan , Walsworth Ronald L. , Westerdale Shawn
Published: November 2023

We outline the unique opportunities and challenges in the search for “ultraheavy” dark matter candidates with masses between roughly 10 TeV and the Planck scale m_{\rm pl} ≈ 10^{16} TeV. This mass range presents a wide and relatively unexplored dark matter parameter space, with a rich space of possible models and cosmic histories. We emphasize that both current detectors and new, targeted search techniques, via both direct and indirect detection, are poised to contribute to searches for ultraheavy particle dark matter in the coming decade. We highlight the need for new developments in this space, including new analyses of current and imminent direct and indirect experiments targeting ultraheavy dark matter and development of new, ultra-sensitive detector technologies like next-generation liquid noble detectors, neutrino experiments, and specialized quantum sensing techniques.
Determining the usefulness of the Copernicus High-Resolution Vegetation Phenology and Productivity Product (HR-VPP) with official agricultural data on cropland in case of the 2018 drought in the Federal State of Saxony, Germany
Authors: Goihl Sebastian
Published: November 2023

Remote sensing-based data on vegetation conditions provide important information for agriculture. In this study, the potential uses of the freely available High-Resolution Vegetation Phenology and Productivity Product (HR-VPP) are tested. This test examines the 2018 drought year in the state of Saxony, Germany, and the capabilities and limitations of the HR-VPP product in use with Integrated Administration and Control System (IACS) data. The results show that field and crop type-specific spatial (re)analyses of a drought are possible and that there is still great potential in this data analysis. Using the data in a new proposed VPP-based Farm-Level Temporal Comparison Indicator (VPP-FLTCI), it was not possible to tease out patterns in why farms applied for state drought aid in 2018 compared to other farms. In the future, even better and more detailed analyses based on the HR-VPP can be expected, as the data series with now a total of 5 years is still very short to generate sufficient references, especially in Central European agriculture, which is characterized by crop rotation.
Cystersi jędrzejowscy po kasacie opactwa w 1819 r. Studium biograficzne, cz. 1
Authors: Stępień Robert
Published: November 2023

Artykuł przedstawia losy cystersów jędrzejowskich po kasacie opactwa w 1819 r. W pierwszym etapie badań przygotowano kartotekę biograficzną zakonników, która posłużyła do przeprowadzenia analizy w zakresie ich pochodzenia społecznego i terytorialnego oraz liczebności i struktury wieku. Podstawowy materiał źródłowy stanowiły akta ogólne i personalne duchowieństwa, schematyzmy diecezjalne i zakonne oraz akta parafialne i księgi metrykalne. Po supresji opactwa niektórzy z zakonników pozostali dożywotnio w zabudowaniach klasztoru, inni przeszli do pracy na placówkach parafialnych. Niejednokrotnie były to ośrodki powiązane z klasztorem jędrzejowskim.
Zastosowanie metody georadarowej w badaniach dawnej architektury: relikty gotyckiego kościoła w Trzygłowie (gm. Gryfice)
Authors: Welc Fabian
Published: November 2023

Metoda georadarowa jest od wielu lat stosowana z powodzeniem w archeologii. Zaczyna być również standardem w nieinwazyjnych badaniach dawnej architektury. Największym problemem w implementacji tej metody na stanowiskach z reliktami architektonicznymi są rozległe warstwy gruzu, niwelacje, roślinność oraz elementy infrastruktury, które znacząco utrudniają pomiar oraz interpretację uzyskanych wyników. Pomimo tych ograniczeń, prawidłowo zaplanowane i wykonane badania georadarowe, nawet na niewielkim obszarze, mogą dostarczyć bardzo istotnych informacji dotyczących znajdujących się pod ziemią pozostałości dawnych budowli. Co więcej, wyniki profilowania georadarowego zintegrowane z danymi historycznymi pozwalają na trójwymiarową rekonstrukcję niezachowanego na powierzchni ziemi zabytku. Przykładem mogą być prezentowane w niniejszym artykule wyniki badań georadarowych reliktów gotyckiego kościoła św. Elżbiety w Trzygłowie (dawniej Trieglaff – wieś w gminie Gryfice, północno-zachodnia Polska). Świątynię tą rozebrano w 1955 roku. Wyniki rozpoznania geofizycznego w połączeniu z kwerendą materiałów archiwalnych pozwoliły na zobrazowanie przestrzenne (3D) wyglądu nieistniejącego już kościoła i niejako ponowne przywrócenie go lokalnej społeczności. Zaprezentowane tu podejście powinno być standardem w badanych architektonicznych zabytkowych budowli z użyciem metod nieinwazyjnych, co autor niniejszego opracowania proponuje określić terminem geofizyka architektury.
The Radiosensitizing Potentials of Silymarin/Silibinin in Cancer: A Systematic Review
Authors: Gupta Jitendra , Jalil Abduladheem Turki , Riyad Muedii Zainab Al-hawraa , Aminov Zafar , Alsaikhan Fahad , Ramírez-Coronel Andrés Alexis , Ramaiah Pushpamala , Farhood Bagher
Published: November 2023

Introduction:

Although radiotherapy is one of the main cancer treatment modalities, exposing
healthy organs/tissues to ionizing radiation during treatment and tumor resistance to ionizing
radiation are the chief challenges of radiotherapy that can lead to different adverse effects. It
was shown that the combined treatment of radiotherapy and natural bioactive compounds (such as
silymarin/silibinin) can alleviate the ionizing radiation-induced adverse side effects and induce
synergies between these therapeutic modalities. In the present review, the potential radiosensitization
effects of silymarin/silibinin during cancer radiation exposure/radiotherapy were studied.

Methods:

According to the PRISMA guideline, a systematic search was performed for the identification
of relevant studies in different electronic databases of Google Scholar, PubMed, Web of
Science, and Scopus up to October 2022. We screened 843 articles in accordance with a predefined
set of inclusion and exclusion criteria. Seven studies were finally included in this systematic
review.

Results:

Compared to the control group, the cell survival/proliferation of cancer cells treated with
ionizing radiation was considerably less, and silymarin/silibinin administration synergistically increased
ionizing radiation-induced cytotoxicity. Furthermore, there was a decrease in the tumor
volume, weight, and growth of ionizing radiation-treated mice as compared to the untreated
groups, and these diminutions were predominant in those treated with radiotherapy plus silymarin/
silibinin. Furthermore, the irradiation led to a set of biochemical and histopathological changes
in tumoral cells/tissues, and the ionizing radiation-induced alterations were synergized following
silymarin/silibinin administration (in most cases).

Conclusion:

In most cases, silymarin/silibinin administration could sensitize the cancer cells to
ionizing radiation through an increase of free radical formation, induction of DNA damage, increase
of apoptosis, inhibition of angiogenesis and metastasis, etc. However, suggesting the use of
silymarin/silibinin during radiotherapeutic treatment of cancer patients requires further clinical
studies.
The Roles of Endogenous D2R Dopamine and μ-opioid Receptors of the Brain in Alcohol use Disorder
Authors: Khikhmetova Kamila , Semenova Yuliya , Bjørklund Geir
Published: November 2023

:

Alcohol use disorder (AUD) affects millions of people worldwide. It is characterized
by a strong physiological and psychological craving to consume large amounts
of alcohol despite adverse consequences. Alcohol use disorder carries a large health and
economic burden on society. Despite its prevalence, AUD is still severely undertreated.
The precise molecular mechanisms of how alcohol addiction forms are yet unknown.
However, previous studies on animal models show that along with the μ-opioid receptors,
the D2R dopamine receptors may also be involved in alcohol craving and reward
pathways. Currently, there is a limited number of treatment strategies for alcohol use disorder,
which include several medications and therapy. By understanding the limitations
of current treatment options and exploring new potential targets, it could be possible to
find more effective ways of treating AUD in the future.
AI-driven Discovery of Celecoxib and Dexamethasone for Exploring their Mode of Action as Human Interleukin (IL-6) Inhibitors to Treat COVID-19-induced Cytokine Storm in Humans
Authors: Shamkh Israa M. , Elkazzaz Mahmoud , Radwan Enas. S. , Najeeb Jawayria , Rehman Md. Tabish , AlAjmi Mohamed F. , Shahwan Moayad , Sufyan Muhammad , Alaqeel Nouf Khalifa , Ibrahim Ibrahim A. , Jabbar Basit , Khan Mohammad Shahbaz , Karpiński Tomasz M. , Haikal Abdullah , Aljowaie Reem M. , Almutairi Saeedah Musaed , Ahmed Amr
Published: November 2023

Background::

In the case of COVID-19 patients, it has been observed that the immune system of
the infected person exhibits an extreme inflammatory response known as cytokine release syndrome (CRS)
where the inflammatory cytokines are swiftly produced in quite large amounts in response to infective stimuli.
Numerous case studies of COVID-19 patients with severe symptoms have documented the presence of higher
plasma concentrations of human interleukin-6 (IL-6), which suggests that IL-6 is a crucial factor in the pathophysiology
of the disease. In order to prevent CRS in COVID-19 patients, the drugs that can exhibit binding
interactions with IL-6 and block the signaling pathways to decrease the IL-6 activity may be repurposed.

Methods::

This research work focused on molecular docking-based screening of the drugs celecoxib (CXB)
and dexamethasone (DME) to explore their potential to interact with the binding sites of IL-6 protein and reduce
the hyper-activation of IL-6 in the infected personnel.

Results::

Both of the drugs were observed to bind with the IL-6 (IL-6 receptor alpha chain) and IL-6Rα receptor
with the respective affinities of -7.3 kcal/mol and -6.3 kcal/mol, respectively, for CXB and DME. Moreover,
various types of binding interactions of the drugs with the target proteins were also observed in the docking
studies. The dynamic behaviors of IL-6/IL-6Rα in complex with the drugs were also explored through molecular
dynamics simulation analysis. The results indicated significant stabilities of the acquired drug-protein
complexes up to 100 ns.

Conclusion::

The findings of this study have suggested the potential of the drugs studied to be utilized as antagonists
for countering CRS in COVID-19 ailment. This study presents the studied drugs as promising candidates
both for the clinical and pre-clinical treatment of COVID-19.
Combinatorial Synthesis of Indole Derivatives as Anti-oomycetes Agents
Authors: Hai Fei , Wei Ruxue , Li Yan , Wang Ruiguang , Tian Yuee , Liu Shengming , Chen Genqiang , Che Zhiping
Published: November 2023

Background:

Developing high-efficiency and low-risk small-molecule green fungicide
is the key to effective control of the plant pathogenic oomycetes. Indole is an important raw
material for drug synthesis. Due to its unique structural skeleton, indole, and its derivatives have
exhibited a wide range of biological activities. However, a study on the synthesis of novel indole
derivatives as fungicidal agents against Phytophthora capsici has not yet been reported.

Methods:

The important intermediates 2a-c and 3a-c were synthesized in high yields by Vilsmeier-
Haack and Knoevenagel reactions with indole as the lead compound. Furthermore, different
substituted benzenesulfonyl groups were introduced into the NH position of the indole ring,
and twelve indole derivatives (I-a-l) were prepared. Their structures were well characterized by
1H NMR, HRMS, and melting point.

Results:

The results showed that 2-[(N-(4-nitrobenzenesulfonyl)-indole-3)-methylene]-diethyl
malonate (I-d) and 2-[(N-(4-nitrobenzenesulfonyl)-5-cyanoindole-3)-methylene]-diethyl malonate
(I-l) showed more anti-oomycete activity against P. capsici than the commercialized fungicide
zoxamide, with corresponding EC50 values of 26.53, 23.48 and 28.16 mg/L, respectively,
and the protective effect of the compounds against P. capsici in vivo further confirmed the above
results.

Conclusion:

The preliminary structure-activity relationship showed that the formyl group modification
at the C-3 position of the indole ring was acceptable, and the different anti-oomycete activities
of R1 and R2 were significantly different, with R1 being 5-CN > H > 6-Me, and R2 being
4-NO2 > 3-NO2, H > 4-Me.
Bioconjugation Techniques for Enhancing Stability and Targeting
Efficiency of Protein and Peptide Therapeutics
Authors: Bisht Tanuja , Adhikari Anupriya , Patil Shivanand , Dhoundiyal Shivang
Published: November 2023

Bioconjugation techniques have emerged as powerful tools for enhancing the stability
and targeting efficiency of protein and peptide therapeutics. This review provides a comprehensive
analysis of the various bioconjugation strategies employed in the field. The introduction highlights
the significance of bioconjugation techniques in addressing stability and targeting challenges
associated with protein and peptide-based drugs. Chemical and enzymatic bioconjugation
methods are discussed, along with crosslinking strategies for covalent attachment and site-specific
conjugation approaches. The role of bioconjugation in improving stability profiles is explored,
showcasing case studies that demonstrate successful stability enhancement. Furthermore, bioconjugation
techniques for ligand attachment and targeting are presented, accompanied by examples
of targeted protein and peptide therapeutics. The review also covers bioconjugation approaches for
prolonging circulation and controlled release, focusing on strategies to extend half-life, reduce
clearance, and design-controlled release systems. Analytical characterization techniques for bioconjugates,
including the evaluation of conjugation efficiency, stability, and assessment of biological
activity and targeting efficiency, are thoroughly examined. In vivo considerations and clinical
applications of bioconjugated protein and peptide therapeutics, including pharmacokinetic and
pharmacodynamic considerations, as well as preclinical and clinical developments, are discussed.
Finally, the review concludes with an overview of future perspectives, emphasizing the potential
for novel conjugation methods and advanced targeting strategies to further enhance the stability
and targeting efficiency of protein and peptide therapeutics.
N-acetylation of Aromatic Amines by One-pot Route
Authors: Guo Zhongqi , Fan Wenxu , Ablajan Keyume
Published: November 2023

In this study, a simple one-pot synthesis of acetamides from aromatic amines and acetonitrile
in the presence of H2O and K2S2O8 is presented. The reaction proceeds in a mixed solvent
(CH3CN: DMSO, 3:1) without using metals or toxic reagents. Various N-acetanilides are obtained
with 53-91% yields. The method is selective for aromatic amines, with aliphatic amines remaining intact.
This represents a new, efficient, and economical method for the synthesis of a range of acetamides.
Screening and Analysis of Skin Cancer Treatment Using Biocomponents of
Plants Using Backpropagation Neural Networks: A Comprehensive Review
Authors: Soni Urvashi , Gupta Jeetendra Kumar , Singh Kuldeep , Khandelwal Girdhar
Published: November 2023

:

In recent years, the use of natural compounds derived from plants for the treatment of skin
cancer has gained significant attention due to their potential therapeutic effects and minimal side effects.
This review focuses on the innovative approach of utilizing biocomponents sourced from plants
in combination with backpropagation neural networks (BPNN) for the screening and analysis of skin
cancer treatments. The integration of plant-derived compounds and AI-driven algorithms holds promise
for enhancing the precision and effectiveness of skin cancer therapies. The review begins by highlighting
the escalating global burden of skin cancer and the limitations of conventional treatment approaches.
With the rise in concerns about the adverse effects of synthetic drugs, researchers have
turned their attention towards exploring the therapeutic potential of plant-derived biocomponents.
These natural compounds are known for their rich bioactive constituents that exhibit anti-cancer
properties, making them suitable candidates for skin cancer treatment. One of the key challenges in
harnessing the potential of plant-derived compounds is the need for accurate screening and analysis
of their effects. This is where backpropagation neural networks, a type of artificial neural network,
comes into play. These networks can process complex data and recognize intricate patterns, enabling
them to predict the efficacy of various biocomponents in combating skin cancer. The review delves
into the functioning of BPNN and its applications in drug discovery and treatment evaluation. Furthermore,
the review explores several case studies that demonstrate the successful integration of
plant-derived compounds with BPNN in the context of skin cancer treatment. These studies provide
evidence of how this synergistic approach can lead to improved treatment outcomes by minimizing
adverse effects and maximizing therapeutic benefits. The methodology section discusses the steps
involved in training the neural network using relevant datasets and optimizing its performance for
accurate predictions. While the integration of plant-derived compounds and BPNN shows great
promise, the review also addresses the existing challenges and limitations. These include the need for
comprehensive and standardized datasets, potential biases in training data, and the complexity of neural
network architectures. The regulatory considerations surrounding plant-based therapies are also
discussed, highlighting the importance of rigorous testing and validation.
Diabetic Retinopathy: Clinical Features, Risk Factors, and Treatment
Options
Authors: Mishra Sudhanshu , Vishwakarma Pratik Kumar , Tripathi Mridani , Ojha Smriti , Tripathi Shivendra Mani
Published: November 2023

Diabetic retinopathy is a common complication of diabetes that affects the eyes and
can lead to severe vision loss or blindness if left untreated. Chronic hyperglycemia destroys the
blood vessels in the retina, resulting in diabetic retinopathy. The damage can lead to leakage of
fluid and blood into the retina, causing edema, hemorrhages, and ischemia. A thorough evaluation
by an ophthalmologist is necessary to determine the most appropriate course of treatment
for each patient with diabetic retinopathy. The article discusses various surgical treatment options
for diabetic retinopathy, including vitrectomy, scleral buckling, epiretinal membrane peeling,
retinal detachment repair, and the risk factors of diabetic retinopathy. These surgical techniques
can help to address the underlying causes of vision loss and prevent further complications
from developing or worsening. To avoid complications and maintain vision, this review emphasizes
the significance of early detection and treatment of diabetic retinopathy. Patients with diabetic
retinopathy can improve their eyesight and quality of life with the help of some surgical
treatments. The article also highlights some case studies in the field of diabetic retinopathy.
A Mechanistic Approach on Structural, Analytical and Pharmacological
Potential of Beta-sitosterol: A Promising Nutraceutical
Authors: Dwivedi Jyotsana , Sachan Pranjal , Wal Pranay
Published: November 2023

Phytosterols are bioactive substances that are found spontaneously in the cell membranes
of plants and have an atomic composition similar to cholesterol produced by vertebrate
cells. They are widely distributed in dietary lipids from plants such as nuts, seeds, and beans with
olive oil. β-sitosterol has a variation of pharmacological belongings, with analgesic, immunomodulatory,
antiseptic, antineoplastic, anti-inflammatory, cholesterol decreasing, hepatoprotective, and
protecting action concerning respiratory and non-alcoholic fatty liver disease illnesses, antioxidant,
and anti-diabetic activity. Clinical studies on humans have shown that it works against prostate
cancer and has anti-inflammatory and anti-cancer properties. Pharmacological testing of β-sitosterol
demonstrated a range of actions including antibacterial, anti-inflammatory, antinociceptive,
anticancer, antifertility, angiogenic, antioxidant, immunomodulatory, diabetes-fighting, and
anticancer without significant toxicity. Several formulations have been created by numerous authors,
but there are few scholarly reviews of the analytical, pharmacology, and phytochemistry
methodologies for this molecule. In this review the literature on β-sitosterol, its biosynthesis, pharmacology,
nutraceutical applications, toxicity, formulations, and analytical techniques are all highlighted.
Wound Healing, Anti-inflammatory and Antioxidant Potential of Quercetin
Loaded Banana Starch Nanoparticles
Authors: Kumar Dharmendra , Sharma Pramod Kumar
Published: November 2023

Background:

Quercetin belongs to the BCS Class IV of drugs, which means it ex-hibits low solubility and low permeability. Quercetin is a potent antioxidant drug candidate, but it has several drawbacks, such as a short half-life, poor stability, bioavailability, and solubility. These factors affect its reliability as a good wound-healing, anti-inflammatory, and antioxidant agent. Quercetin nanoparticles resolved these problems and offered high stability, high encap-sulation efficacy, sustained and prolonged release, and enhanced accumulation at target sites with high therapeutic efficacy.

Methods:

Banana starch and quercetin were used to formulate a new composition of nanoparti-cles. Formulated QBSN were evaluated for their antioxidant, wound healing, and anti-inflam-matory potential.

Results:

QBSN showed a good antioxidant effect against the DPPH free radical scavenging model. Inhibition of DPPH free radicals reached up to 98 percent at 40 μl. Histopathological studies of treated tissues (wound and paw edema) confirmed the potential of QBSN.

Conclusion:

In the future, prepared nanoparticles may be the choice of drug formulation for wound healing, anti-inflammatory therapy, and antioxidant therapy.
Combined Administration of Metformin and Vitamin D: A Futuristic Approach for Management of Hyperglycemia
Authors: Tyagi Sakshi , Mani Shalini
Published: November 2023

:

Diabetes is a series of metabolic disorders that can be categorized into three types depending
on different aspects associated with age at onset, intensity of insulin resistance, and beta-
cell dysfunction: Type 1 and 2 Diabetes, and Gestational Diabetes Mellitus. Type 2 Diabetes
Mellitus (T2DM) has recently been found to account for more than 85% of diabetic cases. The
current review intends to raise awareness among clinicians/researchers that combining vitamin
D3 with metformin may pave the way for better T2DM treatment and management. An extensive
literature survey was performed to analyze vitamin D’s role in regulating insulin secretion, their
action on the target cells and thus maintaining the normal glucose level. On the other side, the
anti-hyperglycemic effect of metformin as well as its detailed mechanism of action was also
studied. Interestingly both compounds are known to exhibit the antioxidant effect too. Literature
supporting the correlation between diabetic phenotypes and deficiency of vitamin D was also explored
further. To thoroughly understand the common/overlapping pathways responsible for the
antidiabetic as well as antioxidant nature of metformin and vitamin D3, we compared their antihyperglycemic
and antioxidant activities. With this background, we are proposing the hypothesis that
it would be of great interest if these two compounds could work in synergy to better manage the
condition of T2DM and associated disorders.
Metabolic Disorder Therapeutics and their Effects on Memory
Authors: Aggarwal Punita , Khan Faiz , Banerjee Sugato
Published: November 2023

abstract:

Diabetes is one of the major metabolic disorders of this era. It not only impacts a person's
lifestyle but also has a long-term impact on the brain. It has a detrimental effect on a person's health
when combined with hypertension and hyperlipidaemia. Several studies have suggested that the incidence
of dementia is higher in people with metabolic syndrome. Investigations are underway to
determine whether antidiabetic, hypolipidemic, hypercholesteraemic, anti-hypertensive, and other
combination medicines can minimize the incidence of cognitive impairment. Some studies have
suggested that anti-diabetic drugs like metformin, liraglutide, and dapagliflozin might enhance
memory in long-term users. At the same time, other studies indicate that long-term insulin use may
cause memory decline. Similarly, drugs like ACEIs, CCBs, fibrates, statins, and various nutraceuticals
have been shown to improve cognition via multiple mechanisms. Literature suggests that drugs
that can treat metabolic syndrome can also partially reduce the accumulation of beta-amyloid,
whereas some studies contradict these findings. We review the past thirty years' of research work
and summarize the effects of most commonly used drugs and nutraceuticals for treating metabolic
syndrome on memory. Here, we review the effects of antidiabetic, hypolipidemic, anti-hypertensive,
and hypercholesteremic, and their combination in learning and memory.
Current Perspective and Mechanistic Insights on Bioactive Plant Secondary
Metabolites for the Prevention and Treatment of Cardiovascular Diseases
Authors: Grewal Jyotika , Kumar Vijay , Gandhi Yashika , Rawat Hemant , Singh Ravindra , Singh Arjun , Narasimhaji Ch. V. , Acharya Rabinarayan , Mishra Sujeet K
Published: November 2023

Cardiovascular diseases (CVDs) are one of the most prevalent medical conditions of
modern era and are one of the primary causes of adult mortality in both developing and developed
countries. Conventional medications such as use of aspirin, beta-blockers, statins and angiotensin-
converting enzyme inhibitors involve use of drugs with many antagonistic effects.
Hence, alternative therapies which are safe, effective, and relatively cheap are increasingly being
investigated for the treatment and prevention of CVDs. The secondary metabolites of medicinal
plants contain several bioactive compounds which have emerged as alternatives to toxic modern
medicines. The detrimental effects of CVDs can be mitigated via the use of various bioactive
phytochemicals such as catechin, isoflavones, quercetin etc. present in medicinal plants. Current
review intends to accumulate previously published data over the years using online databases
concerning herbal plant based secondary metabolites that can help in inhibition and treatment of
CVDs. An in-depth review of various phytochemical constituents with therapeutic actions such
as antioxidant, anti-inflammatory, vasorelaxant, anti-hypertensive and cardioprotective properties
has been delineated. An attempt has been made to provide a probable mechanistic overview
for the pertinent phytoconstituent which will help in achieving a better prognosis and effective
treatment for CVDs.
Research Progress of Selective Laser Melting Forming Medical Implants
Authors: Gao Bingwei , Sun Zhixin , Yu Hongtao , Peng Liqing , Zhao Hongjian
Published: November 2023

Selective laser melting technology has the advantages of rapid manufacture, high precision,
and the ability to produce fine structures. Medical implants made using selective laser melting
technology have high precision and excellent mechanical properties that meet the needs of patients
and make medical implants more promising in the medical field. This paper reviews the
progress of research on selective laser melting of medical implants. This paper draws on numerous
journals and patents. This paper firstly reviews the classification of medical implants, mainly
including hip implants, knee implants, maxillo-craniofacial implants and spinal implants. Secondly,
the common porous structure design methods, the effect of porous structure on the mechanical
properties of the implant, and the effect of pore structure on the growth properties of porous titanium
alloy bone are summarised. Finally, the process of manufacturing titanium alloy implants by
selective laser melting technology is described. Medical implants made by selective laser melting
have excellent properties and are widely used in the medical field. Compared to traditional mechanical
processing methods, selective laser melting technology can better preserve the properties
of the raw material, while providing higher precision and faster preparation. However, selective
laser melting has a number of drawbacks, including differences in material microstructure, reduced
strength and plasticity, inadequate surface treatment, and enhanced safety and reliability.
Further scientific research and technological innovation are needed to solve these problems. In the
future, as technology continues to innovate and develop, SLM technology will become more mature,
resulting in implants that are more natural, suitable for the body and long-lasting. At the
same time, as implants are personalised, there will be a huge market demand and development
opportunities. In addition, the continuous improvement of regulatory policies is expected to further
promote the market development and application of medical implants.
Arsenic Exposure and Amyloid Precursor Protein Processing: A Focus on
Alzheimer's Disease
Authors: Sharma Ravikant , Abubakar Md. , Bisht Priya , Rachamalla Mahesh , Kumar Arun , Murti Krishna , Ravichandiran Velayutham , Kumar Nitesh
Published: November 2023

Background::

Arsenic is present in above permissible safe limits in groundwater, soil, and food, in various areas of the world. This is increasing exposure to
humankind and affecting health in various ways. Alternation in cognition is one among them. Epidemiological research has reflected the impact of
arsenic exposure on children in the form of diminished cognition.

Aims::

Considering this fact, the present study reviewed the impact of arsenic on amyloid precursor protein, which is known to cause one of the
commonest cognitive disorders such as Alzheimer’s disease.

Methods::

The present study reviews the arsenic role in the generation of amyloid-beta from its precursor that leads to Alzheimer’s disease through the
published article from Pubmed and Scopus.

Description::

According to the findings, regular, long-term exposure to arsenic beginning in infancy changes numerous arsenic level-regulating regions in the rat
brain, which are related to cognitive impairments. Arsenic also affects the BBB clearance route by increasing RAGE expression. Arsenic triggers
the proamyloidogenic pathway by increasing APP expression and subsequently, its processing by β-secretase and presenilin. Arsenic also affects
mitochondrial dynamics, DNA repair pathway and epigenetic changes. The mechanism behind all these changes is explained in the present review
article.

Conclusion::

A raised level of arsenic exposure affects the amyloid precursor protein, a factor for the early precipitation of Alzheimer’s disease.
Implementation of a Robust Framework for Low Power Approximate
Multiplier Using Novel 3:2 and 4:2 Compressor for Image Processing
Applications
Authors: Thakur Garima , Sohal Harsh , Jain Shruti
Published: November 2023

Background:

The technique of approximation allows for a trade-off between accuracy,
speed, area use, and power usage. It is essential in applications that can withstand errors because
even a modest accuracy loss can have a significant impact on the result.

Methods:

In this research, a novel approximate adder and exact 3:2 and 4:2 compressors are used to
create a power-efficient approximation multiplier. In order to reduce the partial product while keeping
a fair level of accuracy, approximate compressors are used.

Results:

The proposed approximate multiplier performs better in terms of LUTs, area, memory usage,
and power consumption when compared to state-of-the-art work.

Conclusion:

The proposed approximate multiplier is applied to two sets of images for image blending
to validate the results. PSNR values of 25.49 dB and 24.7 dB were attained for set 1 and set 2,
respectively.
A Study on Underwater Image Processing Techniques
Authors: Choudhary Nishant , Goel Neha , Yadav Ravindra Kumar
Published: November 2023

In recent years, a potential interest has been developed in exploring and enhancing the
quality of underwater images. The captured underwater images often experience scattering and high
levels of noise due to the properties of light transit within the water and the biotic movement that occurs
inside the ocean bottom. Underwater cameras or devices were fitted inside the unmanned underwater
vehicles (UUVs), autonomous underwater vehicles (AUVs), remotely operated vehicles
(ROVs), ocean detector networks, etc to see the ocean bottom. Despite being a crucial detector for
keeping an eye on underwater landscapes, modern underwater camera sensors or detectors contain a
number of problems. Numerous solutions to the issues with conventional underwater photography
have been put out during the last five years. With the help of the number of contributions and difficulties
reported by more than 40 researchers in their research article, this study focused to mention
the current underwater image processing methods. This article represents an overview of numerous
underwater image-processing techniques utilized, including underwater picture de-scattering, underwater
image colour refurbishment, and underwater image aspect evaluations. Also, the latest trends,
problems, and challenges for creating and processing underwater image sensors were discussed.
Social Media and Fear of Missing Out: An Exploration of the
Role of Mindfulness, Cognitive Biases and Need to Belong in
Chinese College Students
Authors: Li Jing , Liu Sijia
Published: November 2023

Background:

Fear of Missing Out (FoMO) on social media has emerged as
a significant concern, particularly among college students, with implications for mental
well-being and internet use. While previous studies have explored various aspects of
mindfulness about digital behaviors, the specific link between mindfulness and FoMO,
as well as the potential mechanisms involved, remains underexplored.

Objective:

Guided by the Conservation of Resources (COR) theory and the
Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study
investigates the relationship between mindfulness and FoMO among Chinese college
students. Additionally, it explores the mediating roles of cognitive bias and the need
to belong in understanding how mindfulness influences FoMO.

Methods:

Data was collected from 748 university students from two universities in
China. Participants completed questionnaires assessing mindfulness, cognitive bias, the
need to belong, and FoMO. Statistical analyses, including mediation models and
bootstrapping, were conducted using SPSS 25.0 and the PROCESS macro version 3.3.

Results:

The SPSS PROCESS macro Model 4 analysis revealed that the relationships
between mindfulness and FoMO (β=-.011, p=.738) and between Attention to Positive
Information (API) and FoMO (β=.029, p=.383) were nonsignificant. Mindfulness
exhibited negative associations with Attention to Negative Information (ANI) (β=-
.250, p<.001) and the need to belong (β=-.254, p<.001) and positive associations with
API (β=.268, p<.001). Furthermore, ANI positively correlated with FoMO (β=.182,
p<.001), and the need to belong had a significant positive impact on FoMO (β=.503,
p<.001). The mediation analysis indicated that the effect of mindfulness on FoMO
was fully mediated by ANI and the need to belong, with no direct effect through API.

Conclusion:

By recognizing mindfulness as a valuable psychological resource, this
research offers insights for developing targeted interventions aimed at reducing
FoMO and promoting healthier social media engagement among this population.
These findings contribute to the broader understanding of the interplay between
mindfulness, cognitive processes, motivation, and FoMO, offering guidance for
future research and practical interventions.