bluuebunny/crossref_metadata_2025 huggingface dataset:
PROBLEMATIKA PRILAKU NARSISTIK PADA REMAJA DALAM BERMEDIA SOSIAL
Authors: Saudah Saudah
Published: February 2023

Maraknya perilaku narsistik dikalangan remaja terjadi bukan tanpa sebab. Perilaku ini sering kali dikaitkan dengan penggunaan media sosial yang dapat dengan mudah diakses oleh kalangan muda mudi saat ini. Perilaku narsistik dapat menjadi masalah ketika orang mementingkan diri sendiri, terlalu mengagumi persetujuan orang lain, dan acuh tak acuh terhadap kepekaan orang lain. Metode penelitian yang digunakan dalam artikel ini adalah dengan metode studi literatur. Data yang digunakan pada artikel ini bersumber dari jurnal, artikel ilmiah, hasil penelitian berupa skripsi serta literatur lain yang memuat tentang perilaku narsistik pada remaja. Berdasarkan hasil studi literatur, munculnya perilaku narsistik pada remaja ketika mereka merasa tidak nyaman dan memiliki harga diri yang rendah, sehingga mereka melakukan perilaku narsis untuk mendapatkan kenyamanan dan penghargaan dari orang lain. Narsistik yang terjadi pada remaja muncul ketika mereka merasa tidak nyaman pada diri sendiri, mencari perhatian, kebutuhan untuk dikagumi dan beberapa faktor lain. Jika dibiarkan berlarut-larut, tentu akan membuat individu tidak bahagia dan semakin bingung karena segala macam emosi berkecamuk di dalam dirinya.
Pain and Depression Levels Related to the Quality of Life in Elderly People with Chronic Non-Specific Low Back Pain?
Authors: YAMAN Fatıma , AKSOY Cihan Caner , AKDENİZ LEBLEBİCİER Merve , SAHİN Emre
Published: February 2023

This study aimed to investigate the relationship between pain severity and depression level and quality of life in elderly patients with chronic non-specific low back pain (CNLBP) and determine the effect of age group on the quality of life, pain severity and depression symptom levels of patients. Evaluation parameters were obtained using scales specific to geriatric patients. Pain severity, depression, and quality of life were evaluated using the Geriatric Pain Measure (GPM), Geriatric Depression Scale (GDS), and World Health Organization Quality of Life Questionnaire-Older Adults Module (WHOQOL-OLD), respectively. The study included a total of 231 patients with CNLBP (age ≥65 years), of whom 62.3% (n=144) were female and 37.7% were male (n=87). There was a moderate correlation between the patients’ GDS and GPM scores (r=0.53; p<0.05). GDS also had a moderate correlation with the ‘past-present-and-future activities’ (r=-0.52) and ‘social participation’ (r=-0.48) subdomains of WHOQOL-OLD (p<0.05). According to age groups, the only statistically significant difference was observed in ‘sensory abilities’ (p<0.05). Quality of life is negatively affected by the level of depression and pain intensity in elderly individuals with CNLBP. Evaluation of pain severity and depressive symptom levels in elderly patients with CNLBP may contribute to the establishment of an elderly population with improved quality of life and treatment approach. There is a need for further studies to reveal the reasons for poorer quality of life and increased depression and pain.
A rapid assessment method to estimate the prevalence of ectoparasitoses in Brazil: tungiasis and scabies as case studies
Authors: Heukelbach Jorg , de Sousa Silva Nathiel
Published: February 2023

The epidemiologies of the ectoparasitoses tungiasis and scabies are unknown, and their distribution has not been described systematically in Brazil. We developed a rapid assessment method (RAM) based on an online questionnaire as a new tool to assess the prevalence of tungiasis and scabies and severe disease at the municipality level in the state of Ceará in northeast Brazil. As a first step, online records of tungiasis and scabies were collected from scientific publications, lay media, and the gray literature. Then, an image-based RAM with questions about the prevalence of these diseases, severe diseases, and animal reservoirs was developed as an online open questionnaire. Valid responses were obtained from 1265 respondents, primarily health professionals, from all 184 municipalities in the state. The literature review returned results for only two municipalities. The number of responses from the online questionnaires differed considerably between municipalities (one to 104 responses/municipality). Active contact with municipality health secretariats increased the number of respondents, especially community health agents. The RAM obtained consistent results regarding the prevalence and other epidemiological information. Our approach rapidly obtained primary data on the occurrence of these two important but neglected ectoparasitoses at the municipality level without considerable cost. This approach provides information for planning evidence-based control measures and identifying high-risk areas for focused studies. The RAM can easily be adapted and extended to other settings, countries, and diseases.
An Efficient Logical Average Distance Measure Algorithm (LADMA) to Analyse MRI Brain Images
Authors:   Research Scholar, Department of Computer Applications, Dr. M.G.R. Educational and Research Institute University, Chennai, Mr. A.Naveen , Dr T.Velmurugan ,   Associate ProfessorPG and Research Department of Computer Science, D. G. Vaishnav College, Arumbakkam, Chennai, India
Published: February 2023

Malignant and benign types of tumor infiltrated in human brain are diagnosed with the help of an MRI scanner. With the slice images obtained using an MRI scanner, certain image processing techniques are utilized to have a clear anatomy of brain tissues. Some of such data mining technique is k means and fuzzy C means algorithms. This work proposes a new hybrid algorithm namely LAMDA, which offers successful identification of tumor and perform well for the segmentation of tissue regions in brain. Automatic detection of tumor region in MR (magnetic resonance) brain images has a high impact in helping the radio surgeons assess the size of the tumor present inside the tissues of brain and it also supports in identifying the exact topographical location of tumor region. Experimental results show that the proposed approach reduces the number of features and at the same time it achieves high accuracy level. The observed results to achieve high accuracy level using minimum number of selected features.
Kidney Failure Due to Diabetics – Detection using Classification Algorithm in Data Mining
Authors:   Assistant Professor, Dept.of. Comp. Science, K.C.S Kasi Nadar College of Arts and Science, Chennai, Ms J.Vijayalakshmi
Published: February 2023

In order to analyse the chosen data from various points of view, data mining is used as the effective process. This process is also used to sum up all those views into useful information. There are several types of algorithms in data mining such as Classification algorithms, Regression, Segmentation algorithms, association algorithms, sequence analysis algorithms, etc.,. The classification algorithm can be used to bifurcate the data set from the given data set and foretell one or more discrete variables, based on the other attributes in the dataset. The ID3 (Iterative Dichotomiser 3) algorithm is an original data set S as the root node. An unutilised attribute of the data set S calculates the entropy H(S) (or Information gain IG (A)) of the attribute. Upon its selection, the attribute should have the smallest entropy (or largest information gain) value. The prime objective of this paper is to analyze the data from a Kidney disorder due to diabetics by using classification technique to predict class accurately.
A Fuzzy Clustering Based Approach for Heavy Tail Weight in Web Data
Authors:   Research Scholar, Department of Computer Science, Muthurangam Government Arts College, Vellore, Ms Janani K
Published: February 2023

A distributed frameworks cluster is a gathering of machines that are for all intents and purposes or topographically isolated and that cooperate to give a similar services or application to customers in web application. It is conceivable that huge numbers of the services you keep running in your system today are a piece of a distributed system cluster. Cluster is a vital information mining procedure which expects to isolate the information objects into important gatherings called as groups. It is the way toward gathering objects into bunches to such an extent that items from a similar group are comparable and objects from various groups is unique. In information mining, information bunching has been examined for long time utilizing diverse calculations and ordinary patterns are proposed for better results around tailed data. The fuzzy semantic strategy is look at to group the overwhelming followed information by utilizing some technique for remove. An appraisal thinks about is introduced in view of time and exactness. In this method proposed here is evaluated to other relational clustering schemes using various propinquity matrices as input. Simulations demonstrate the scheme to be very effectual.
The Review on About the Mahatma Gandhi NREGA Analysis using Data Mining Techniques
Authors:   Assistant Professor, PG & Research Department of Computer Applications, St Josephs College of Arts and Science, Cuddalore, Bernard Z John
Published: February 2023

The Indian government is familiarizing many schemes of the encouragement of poor but they are not embracing them in a felicitous and convenient path. There is ambivalence or inadequacy scrutinize in materialized schemes. The system of MGNREGA is one of the expedient materialized by the governance of India in preservation sense that �The spirit Of India Lives in Its rural community�, uttermost of the populace in the imagined place of rural bliss part of the country is gamble on the tongue-tied sweat of one�s for their endurance. MGNREGA is one of such schemes materialized by the government of India which indent at providing hobby to the poor in rural areas by assigning local work them. Data mining tactics that is categorization, bigotry, classification, clustering, outlier and tendency analysis etc...Are enforced on various district for awkward labium, material and juncture are collected separately and presented in this paper and also analysis of the payment of wages to the workers under MGNREGA scheme.
The Study on Clustering Analysis in Data Mining
Authors:   Professor and Head, Department of Computer Science and Eng., Sriram Engineering College, Chennai, Mr S.Manikandan , Caroline A. Lourdu ,   Research Scholar, Department of Computer Science, Mother Teresa Womens University, Kodaikanal
Published: February 2023

Cluster analysis is the duty of assemblage a set of items in such a manner that items in the same group are more alike to each other than to those in other groups .A collection of data entities can be treated as one group. Whereas undertaking gathering investigation, we first distinct the regular of records into groups based on data association and then assign the tags to the groups. The main advantage of gathering over arrangement is that, it is adaptable to variations and helps single out useful features that distinguishes dissimilar groups. It is a most significant tasks to efficient the data mining, and a common method for numerical data analysis, used in numerous fields. In This paper converse about different types of clustering algorithms such as Partitioning Method, Hierarchical Method Density-based Method, Grid-Based Method, Model-Based Method, and Constraint-based Method.
A Study on Image Denoising using Higher Decomposition Method Based on Wavelet Transform
Authors:   Assistant Professor, Department of Computer Science and Applications, K.C.S. Kasi nadar college of arts & science, Chennai, MS I.Jailingeswari
Published: February 2023

The Wavelet change is in certainty an unbounded arrangement of different changes, contingent upon the legitimacy work utilized for its calculation. Picture generally gets contorted amid securing, preparing and progress. As wavelet change has many preferences over other strategy, for example, best restriction and multiresolution properties. Wavelet change utilized different strategies for picture denoising, for example, Visu Recoil yet this method have hindrance that it deliver over smoothening of picture which causes obscure in the edges. So to defeat such issue we have proposed new strategy by changing the Visu recoil thresholding systems. We have contrasted our proposed strategy and the Visu thresholding strategy on the premise of PSNR esteem for various wavelet families, for example, Haar, Daubechies, Biorthogonal, Symlet and Coiflet.
Cloud Computing � A Next Generation E-Learning Resource
Authors:   Department of Computer Science, St. Britto�s College, Adambakkam, Chennai, MR D. Ganeshbabu
Published: February 2023

Cloud computing is an internet based distributed computing technology which provides Storage, Software, Computational platform, Computational infrastructures on demand as a service to the intended users in reusable fashion and users have to pay according to their consumption of those services. As with rapid growth of the cloud computing architecture usage, more and more industries move their focus from investing into processing power to renting processing power from a specialized vendor. Education field is no different. e-Learning has enormous potential in education. Cloud computing into e-learning is feasible and it can greatly improve the efficiency of investment and the power of management. Computing resources on demand and pay money according to their usage. e-Learnig has a service for education with cloud provided with security
Simultaneous Prediction of Stream-Water Variables Using Multivariate Multi-Step Long Short-Term Memory Neural Network
Authors: Ghoochani Shima , Nazemi Neda
Published: February 2023

Multivariate predictive analysis of the Stream-Water (SW) parameters (discharge, water level, temperature, dissolved oxygen, pH, turbidity, and specific conductance) is a pivotal task in the field of water resource management during the era of rapid climate change. The highly dynamic and evolving nature of the meteorological and climatic features have a significant impact on the temporal distribution of the SW variables in recent days making the SW variables forecasting even more complicated for diversified water-related issues. To predict the SW variables, various physics-based numerical models are used using numerous hydrologic parameters. Extensive lab-based investigation and calibration are required to reduce the uncertainty involved in those parameters. However, in the age of data-informed analysis and prediction, several deep learning algorithms showed satisfactory performance in dealing with sequential data. In this research, a comprehensive Explorative Data Analysis (EDA) and feature engineering were performed to prepare the dataset to obtain the best performance of the predictive model. Long Short-Term Memory (LSTM) neural network regression model is trained using over several years of daily data to predict the SW variables up to one week ahead of time (lead time) with satisfactory performance. The performance of the proposed model is found highly adequate through the comparison of the predicted data with the observed data, visualization of the distribution of the errors, and a set of error matrices. Higher performance is achieved through the increase in the number of epochs and hyperparameter tuning. This model can be transferred to other locations with proper feature engineering and optimization to perform univariate predictive analysis and potentially be used to perform real-time SW variables prediction.
Development of Surface-Modified Mesenchymal Stem Cells with Liposomes via Electrostatic Interactions for Tumor Targeted Drug Delivery
Authors: Kono Yusuke , Kamino Renpei , Hirabayash Soma , Kishimoto Takuya , Hosokawa Mika , Ogawara Ken-ichi
Published: February 2023

Mesenchymal stem cells (MSCs) have the tumor-homing capacity, and therefore MSCs are considered to be a promising drug delivery carrier for cancer therapy. To maintain the viability and activity of MSCs, anti-cancer drugs are preferably modified on the surface of MSCs, rather than directly introduced into MSCs. In this study, we attempted to construct surface-modified MSCs with liposomes as a drug carrier by using magnetic anionic liposome/atelocollagen complexes we previously developed. We observed that large-sized magnetic anionic liposome/atelocollagen complexes were abundantly associated with MSCs via electrostatic interactions under a magnetic field, and its cellular internalization was lower than that of the small-sized complexes. Moreover, the complexes with higher atelocollagen concentration showed lower cellular internalization than the complexes with lower atelocollagen concentration. Based on these results, we succeeded in the efficient surface modification of MSCs with liposome by using large-sized magnetic anionic liposomes complexed with high concentration of atelocollagen. The constructed liposome-modified MSCs showed comparable proliferation rate and differentiation potential to unmodified MSCs. Furthermore, liposome-modified MSCs efficiently adhered to vascular endothelial cells and migrated toward the conditioned medium from cancer cells in vitro. These findings suggest that liposome-modified MSCs could serve as an efficient cell-based drug carrier for tumor targeted delivery.
Experimental and 3D Numerical Investigation on Proppant Distribution in a Perforation Cluster Involving the Artificial Neural Network Prediction
Authors: Qu Hai , Chen Xiangjun , Hong Jun , Xu Yang , Li Chengying , Li Zhelun , Liu Ying
Published: February 2023

Uniform proppant distribution in a cluster and a stage with multiple clusters is a primary objective to optimize fracturing parameters and improve the production from each cluster. Because fracturing slurry is typically pumped at high pressure and rate in fields, it is a big challenge to study proppant transport behavior and distribution characteristics through laboratory experiments. There is still a lack of an effective model to quantitatively evaluate proppant distribution based on an actual wellbore configuration. The objective is to propose a novel method to accurately evaluate the distribution uniformity and quickly optimize fracturing parameters based on field conditions.

This paper conducts particle transport experiments in a horizontal pipe with six holes at the helical distribution. A 3D numerical model coupling of the computational fluid dynamics (CFD) and discrete element method (DEM) is used to study proppant distribution. Proppant distribution is quantitatively evaluated by the proppant transport efficiency (E) and normalized standard deviation (NSD). The effects of 10 parameters are investigated. An artificial neural network (ANN) model is developed to predict proppant distribution in a cluster.

The results identify that proppant distribution among perforations is generally toe-biased in a horizontal wellbore due to a high pumping rate. Proppants with large inertia easily miss the heel-side holes and are suspended to the toe side. The complex vorticity flow carries them to the toe-side perforation regardless of hole orientation. Fluid distribution can significantly change proppant distribution regardless of fluid velocity. The heel-biased fluid distribution leads to the same bias of proppant, and the downward perforations receive more proppants. Proppant transport reaches equilibrium quickly, and the distribution is hard to change unless the injection condition varies. It is a good choice to increase fluid viscosity, add perforation sealers, and inject small mesh proppant, especially for the low density. The ANN model trained by extensive experimental and numerical samples can accurately evaluate proppant distribution uniformity. The study provides an efficient way to optimize injection parameter design and achieve real-time optimization coupled with the fiber-optic downhole diagnostic. It can be a crucial part of artificial intelligence hydraulic fracturing.
Efficacy of Nanoencapsulated Herbal Extracts in the Treatment of Induced Wounds in Animal Models: A Systematic Review Protocol.
Authors: Namuga Catherine , Ocan Moses , Kinengyere Alison Alice , Ssenono Richard , Namisango Eve , Muwonge Haruna , Kirabira JohnBaptist , Mugisha Lawrence , Obuku Ekwaro
Published: February 2023

Background: Wounds inflict pain and affect human health causing high expenditure on treatment and management. Herbal crude extracts are used in traditional medicine as a treatment for wounds and other illnesses. However, the progress in the use of plants has been deterred due to their poor solubility and, poor bioavailability requiring administration at high doses. It has been established that nanoencapsulation of herbal products in nanocarriers (size 1nm to 100nm) such as nanofibers, nanoparticles, nanospheres, and nanoliposomes greatly improves their efficacy. Due to their small and large surface area, nanocarriers are more biologically active, improve bioavailability, protect the drug from deterioration, and release it to the targeted site in a sustainable manner.
Aim: The review aims to collate and appraise evidence on the efficacy of nano encapsulated herbal exracts in the treatment of induced wounds in animal models.
Methods: The review will be protocol-driven and conducted according to the Preferred Preferred Reporting Items for Systematic Reviews and Meta-analysis for Protocols (PRISMA-P) and protocol guidelines for systematic review and meta-analysis for animal intervention studies. The final review will be conducted and reported with reference to (PRISMA) 2020 statement. Studies will be searched in Pub Med, ProQuest, Web of Science, MEDLINE, EMBASE, and Google Scholar. The PRISMA flow criteria will be followed in screening the articles for inclusion. Data extraction form will be designed in Excel spreadsheet 2013 and data extracted based on the primary and secondary outcome. Risk of bias assessment will be done using SYRCLE’s risk of bias tool for animal studies. Data analysis will be done using narrative and quantitative synthesis.
Expected results:
We hope to make meaningful comparisons between the effectiveness of the herb-loaded nanomaterials and other interventions (controls) in the selected studies, based on the primary and secondary outcome measures. We expect that these findings inform clinical practice on whether preclinical studies show enough quality evidence on the efficacy and safety of herbal-loaded nanomaterials that can be translated into clinical trials and further research.
Registration; the protocol was submitted in PROSPERO open-access database on 11th May 2022 with application number 330330.
Healthcare practitioners’ knowledge, attitudes and practices of genetics and genetic testing in low- or middle-income countries - A scoping review
Authors: Walters Sarah , Aldous Colleen , Malherbe Helen
Published: February 2023

Background
It is twenty years since the human genome was published. The role of the primary healthcare practitioner (pHCP) in diagnosing and caring for individuals with genetic conditions is envisioned to increase as this knowledge is applied to enable individualised treatment. It is imperative that their genetics knowledge and practices stay current and in line with local or international guidelines.
Method
This scoping review aimed to identify articles in the peer-reviewed, published literature to understand the knowledge, attitudes and practices of pHCP related to genetics, genetic testing and genetic services. Peer-reviewed, full text, journal articles in English focused on human genetics/genomics knowledge, attitudes and practices in low- or middle-income countries (LMIC) and published between January 1990 to April 2022 were included. Both quantitative and qualitative aspects of the literature were examined.
Results
Twenty-eight articles from 16 LMIC across five World Health Organisation (WHO) -defined regions met the inclusion criteria. The number of articles in LMIC has increased over the years and included articles ranged from 1991 to 2021. The South East Asia Region (SEAR) published the most articles (n=8; 29%) and the Western Pacific Region (WPR) the least (n=2; 7%). Ten countries published only one article each, whereas Brazil published the most (n=6; 22%). Eleven articles reported on single gene disorders (39%) and new technologies of pharmacogenomics and genome editing were reported once each (3%). Nineteen articles included aspects of attitude towards genetics, while eight included practices.
Primary HCP lack of knowledge was evident in genetic diseases, emerging technologies, referral of patients to genetic specialists and clinical guidelines for managing genetic conditions. Attitudes towards genetic services and new technologies were generally positive. Barriers to genetic services identified, included inadequate genetic services and required capacity, financial limitations and religious reasons.
Conclusions
Addressing and implementing education of pHCP is necessary to enable appropriate care for patients and families in need. There is a lack of published literature in LMIC regarding pHCP genetic knowledge, attitudes and practices. More research is required on educational interventions for practising pHCP and how to improve their ability to care for patients and families with genetic conditions.
Solar photo-Fenton optimization at neutral pH for microcontaminant removal at pilot plant scale
Authors: Hinojosa Mercedes , Oller Isabel , Quiroga José María , Malato Sixto , Egea-Corbacho Agata , Acevedo-Merino Asunción
Published: February 2023

The increasing occurrence of micropollutants in natural water bodies has medium to long-term effects on both aquatic life and human health. The aim of this study is to optimize the degradation of two pharmaceutical pollutants of emerging concern: amoxicillin and acetaminophen in aqueous solution at laboratory and pilot scale, by solar photo-Fenton process carried out at neutral pH using EDDS as a complexing agent to maintain iron in solution. The initial concentration of each compound was set at 1 mg/L dissolved in a simulated effluent from a municipal wastewater treatment plant (MWTP). A factorial experimental design and its surface response analysis were used to optimise the operating parameters to achieve the highest initial degradation rate of each target. The evolution of the degradation process was measured by Ultra Performance Liquid Chromatography (UPLC/UV), obtaining elimination rates above 90% for both contaminants. Statistical study showed the optimum concentrations of Fe(III) at 3 mg/L at an Fe-EDDS ratio of 1:2 and 2.75 mg/L H2O2 for the almost complete removal of the target compounds by solar photo-Fenton process. Validation of the experimental design was successfully carried out with actual MWTP effluent spiked with 100µg/L of amoxicillin and acetaminophen at pilot plant scale.
Ultrahigh performance and multifunctional flexible biomimetic electronic whiskers for intelligent perception
Authors: Chen Cheng , Li Xin-Lin , Zhao Shumi , Zhong Chuanyu , Song Yang , Chen Rui , Li Erqiang , Li Zhijun , Liu Jian-Wei
Published: February 2023

The humanoid robots that can operate in complex and extreme environments are capable of detecting and discerning various stimuli by the sensors mimicking the human skin sensory system. Herein, we report a flexible biomimetic electronic whisker that greatly expands the diversity of perception in an extremely simple design, including proximity, temperature, pressure, wind, and vibration, which can also discriminate these perception signals. Notably, the biomimetic whisker fabricated using scalable processes possesses a wide-range measurements of bimodal temperature (-189 oC to 150 oC for object, -85 oC to 60 oC for surroundings) and wind speed (1 m s-1 to 20.4 m s-1), with bending stability (250000 cycles), the response of slight pressure (0.07 mN), and the sense of vibration (1000 Hz). In the frame of machine learning, we finally exploit the sensor to demonstrate the outstanding potential in robotics and human-machine interfaces.
Non-Syndromic Cone-Predominant Retinal Degeneration Associated with Homozygosity for the M390R Mutation in BBS1 Gene
Authors: Neves Emmanuel Rebelo , Carvalho Ana Luísa , Raimundo Miguel , Murta Joaquim Neto , Saraiva Jorge , Silva Rufino , Marques João Pedro
Published: February 2023

Introduction: Bardet-Biedl syndrome (BBS) is ciliopathy characterized by retinal degeneration, truncal obesity, post-axial polydactyly, cognitive impairment, male hypogonadotropic hypogonadism, complex female genitourinary malformations, and renal abnormalities (e.g., renal cysts). BBS has an autosomal recessive inheritance pattern, and the most common disease-causing gene is BBS1, with M390R being the most prevalent mutation. Retinal degeneration in BBS is usually a rod-cone degeneration. Nevertheless, phenotypic variability exists, and cone-rod degeneration has also been reported in BBS1-related disease, as well as non-syndromic retinitis pigmentosa (RP). We present a case of a patient with homozygous M390R mutations and non-syndromic cone-predominant retinal degeneration.
Methods: Case-report conducted at a tertiary-care academic hospital.
Results: A 36-year-old male patient with homozygous M390R BBS1 mutations and no family history of retinal disease or consanguinity began follow-up at age 19, after noticing photophobia. Best-corrected visual acuity (BCVA) was 20/32 OD and 20/25 OS. The fundus showed bilateral temporal wedge-shaped pallor of the optic disc and atrophic maculopathy with foveal depigmentation, which translated to hypoautofluorescence on fundus autofluorescence (FAF). Electroretinography revealed cone-rod dysfunction and center-involving maculopathy. Seventeen years later, BCVA was 20/100 OD and 20/80 OS, and the fundus changes overlapped those at baseline. Nevertheless, a slight enlargement of the atrophic lesions was observed on FAF. Despite a thorough systemic evaluation, including abdominal and renal ultrasound, no other major or secondary features of BBS were found.
Discussion: To the extent of our knowledge, this is the first reported case of non-syndromic cone-predominant retinal degeneration in a patient harboring homozygous M390R BBS1mutations.
Trade Agreements and Tobacco Control Policy: Analysis of the Regulatory Patterns and the Influence of FCTC on Trade agreements from 2001 to 2019
Authors: Chen Tzu-ying , Lin Ying-Jun , Chiang Tung-Liang , Tsai Feng-jen
Published: February 2023

Background: This study aims to analyze the influence of Framework of Convention of Tobacco Control (FCTC) on regulatory patterns of trade agreements from 2001 to 2019.
Methods: A search of trade agreements from‘WTO Regional Free Trade Agreement Database’ using keywords as “tobacco”, “cigarette”, “smoking” and “FCTC” from May to August 2020 resulted in a total sample of 268 trade agreements, from which 69 trade agreements were coded and analyzed. The keywords-located provisions in the trade agreements were categorized as 6 trade measures. The word counts of the provisions containing keyword as FCTC were calculated. Chi-square tests were applied to analyze the differences of regulatory patterns between different time frames. The import and export values (USD) of tobacco products under trade agreements containing the term “FCTC” were further collected from the “International Trade Statistics 2001-2020” for a preliminary understanding of trade flow impacted by FCTC.
Results: Among 69 agreements, the percentage of trade agreements containing keyword as “FCTC” increased significantly from 0% before 2011 to 12% after 2011. A significant decrease of using trade measures as “the exclusion list” was found after 2011 (from 10% to 0). The word counts of provisions containing keyword as FCTC increased from 24 words in 2011 to 164 words in 2018, and the content of the provisions became more concrete over time. There are six trade agreements containing the keyword as “FCTC”, and all these 6 agreements were ratified by European Union (EU). Despite EU ratified trade agreements with “FCTC”, the import and export values of tobacco products between EU and the other party countries increased with time. But the gap of average trade values between trade agreements with and without “FCTC” being widened with time.
Conclusions: As a first study evaluated the impact of FCTC on regulatory patterns of trade agreements, our study results showed that after countries signed trade agreements containing keyword FCTC, the regulatory patterns changed significantly. Further studies are recommended to understand the reason and criteria for incorporating FCTC provisions into trade agreements, especially in the EU.
Genome-wide association study for growth traits in Blanco Orejinegro and Romosinuano cattle
Authors: BEJARANO DIEGO , MARTINEZ RODRIGO , Rocha Juan Felipe Martinez
Published: February 2023

Growth traits are economically important characteristics for the genetic improvement of local cattle breeds. Genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to perform a GWAS to identify genomic regions and genes associated to birth weight, weaning weight adjusted for 240 days, 16-months and 24-months weight in Romosinuano (ROMO) and Blanco Orejinegro (BON) cattle. A single-step genomic-BLUP was implemented using 596 BON and 569 ROMO individuals that were genotyped with an Illumina BovineSNP50 BeadChip. There were 25 regions of interest identified on different sets of chromosomes depending on the breed, with few of them simultaneously associated with two or more growth traits and some were common to both breeds. A total of 173 annotations were found during the gene mapping, with 50 of them being potential candidate genes with known growth-related functions in cattle and other species. On BTA14, a region at 24 – 27 MB where important candidate genes such as LYPLA1, XKR4, TMEM68 and PLAG1 are located, was associated with several growth traits. Another region of interest at 0.40-0.77 MB of BTA23 was identified in both breeds, containing KHDRBS2 as a potential candidate gene influencing body weight. Future studies targeting these areas could provide more knowledge to uncover the genetic architecture underlying growth traits in BON and ROMO cattle. The genomic regions and genes identified in this study could be used to improve the prediction of genetic merit for growth traits in this creole cattle breeds.
Assessing total erythrocyte count as a potential attribute for estimating hemoglobin in Cholistani cattle
Authors: Farooq Umer , Idris Musadiq , Sajjad Nouman , Afzal Muhammad Abrar
Published: February 2023

The present study was devised with an aim of assessing an interrelationship between Total Erythrocyte Count (TEC) and Hemoglobin (Hb) concentration, and assessing the potential of TEC for estimating Hb level in Cholistani cattle (n = 264). The TEC and Hb (HbD) estimation was carried out through veterinary hematology analyzer. The Hb was also calculated as TEC × 3 and was termed as HbC. Scatter-plots were drawn and linear regression was carried out between TEC, HbD, HbC and CHB. The regression prediction equation hence attained was used to deduce corrected hemoglobin (CHb). A significant (P ≤ 0.05) difference was noticed between HbD and HbC. A non-significant (P ≥ 0.05) difference was noticed, however, between HbD and CHb. Tests of level of agreement indicated a higher Cronbach Alpha and Interclass Correlation Coefficient (0.682 for average measures) for HbD and CHb as compared to that for HbD and HbC (0.559 for average measures). A convention of Hb concentration as three times of TEC (×3) is not valid for Cholistani cattle. A different pen-side hematological formula i.e. Hb (g/dL) = 0.66(TEC) + 6.1, however, may provide reliable results for Hb estimation from the TEC in cattle. Using hemocytometry for TEC in the field, all the stakeholders associated with veterinary research, academics and practice may benefit from this formula in resource-poor countries.
Antitumor activity of DABA-containing carboxylate Zn complexes on breast cancer cell line MCF-7
Authors: Liu Wei , Lu Hongmei , Xu Xun , Yuan Kangrui , Yang Xinyi , Tan Xiaojun , Zhang Xueyang , Kun Liu , Wu Dudu , Lu Chengyu , Ruan Yongdui , chen zhi
Published: February 2023

The coordination polymer [Zn2(DABA)3(CH3OH)] (DABA=4-dimethylaminobenzoic acid) (ZP) was obtained by hydrothermal synthesis using DABA and Zn(NO3)2·6H2O as substrates. The exact structure of ZP was confirmed by thermogravimetric analysis (TGA), Fourier transforms infrared spectroscopy (FTIR)， and single-crystal X-ray diffraction. The Cell Counting Kit-8 (CCK-8) assay was used to detect the cytotoxicity of ZP on the following cell types (A549, HepG2, Huh-7, MCF-7, LO2 cells), and the results showed that the complex was significantly toxic to MCF-7 cell line and less toxic to normal hepatocytes LO2. In addition, the cell cycle and mitochondrial membrane potential of the MCF-7 cell line were further measured by flow cytometry, and the experimental results indicated that different concentrations of the drug blocked the cell cycle in the S phase and significantly reduced the mitochondrial membrane potential. Western Blot experiments illustrated that ZP was able to upregulate the expression levels of cleaved PARP, cleaved caspase and bax protein and downregulate the expression level of bcl-2. These results suggest that ZP inhibits tumor cell apoptosis through a mitochondria-mediated pathway, accompanied by the regulation of bcl-2 and caspase family proteins.
Moving Upstream: Health System Partnerships Addressing Social Determinants of Health through Community Wealth Building
Authors: Gusoff Geoffrey M. , Zuckerman David , Pham Bich Ha , Ryan Gery W.
Published: February 2023

Background
Health system interventions addressing social needs such as food and housing generally fail to impact the upstream wealth and power inequities underlying those needs. However, a small number of health systems have begun addressing these upstream inequities by partnering with community wealth building initiatives. These initiatives include community land trusts, resident-owned communities, and worker cooperatives, which provide local residents ownership and control over their housing and workplaces. While these partnerships represent a novel, upstream approach to the social determinants of health, no research has yet evaluated them.
Methods
To assess the current state and key aspects of health system-community wealth building partnerships, we conducted semi-structured interviews with thirty-eight key informants across ten partnerships identified through the Healthcare Anchor Network. To analyze the interviews, we used a two-stage coding process. First, we coded responses based on the phase of the intervention to which they corresponded. Then we assessed responses within each aspect for common themes and variation on salient topics.
Results
We identified themes across four phases of the partnerships – motivation, initiation, implementation, and evaluation. Partnerships were generally motivated by a combination of community needs, such as affordable housing and living wage jobs, and health system interests, such as workforce housing and supply chain resilience. Initiating projects required educating leadership and utilizing de-risking strategies to obtain health system buy-in as well as conducting a health system landscape analysis to identify both internal capacities and external partners. Implementation took various forms, with health systems providing financial capital in the form of grants and loans, social capital in the form of convening funders and other stakeholders, and/or capacity building support in the form of strategic planning or technical assistance resources. To evaluate projects, health systems used process and community-level metrics rather than metrics based on individual health outcomes or returns on investment. Based on best practices from each partnership phase, we provide a road map for health systems to develop effective community wealth building partnerships.
Conclusions
Our findings suggest community wealth building represents a promising and largely untapped approach for health systems to address the upstream causes of poor health.
Quantifying and Mapping the Realized Value of Ecosystem Services in Megacities
Authors: Xu Liyan , Li Jue , Li Yipu
Published: February 2023

Spatial mechanisms significantly influence the delivery of ecosystem services (ES) from the provision to the benefiting parties, and their specific impacts on the realized value of ecosystem services (RVES) are yet to be clarified. In this paper, by introducing distance-decay and landscape configuration variables into a real estate hedonic price model and taking Beijing as an example, we systematically examine the effects of various spatial mechanisms on RVES in an urban setting. Results show that the contribution of ES to real property values is 20.4%, two thirds of which is contributed by spatial factors at various scales. Moreover, the RVES yielded in this paper is about two orders of magnitude higher than that assessed using the conventional “per unit-area ES value” approach, which hints at a very different picture of ES value distribution when the realization, rather than the sole provision of ES values is concerned.
Long-lived Quantum State Storage Based on Coherent Mechanical Excitations
Authors: Liu Yulong , Liu Qichun , Sun Huanying , Chen Mo , Wang Shuai-Peng , Li Tie-Fu
Published: February 2023

Mechanical resonators, their capability to host ultralong-lived phonon modes, are particularly attractive for quantum state storage and as memory elements in conjunction with quantum computing and communication devices. Here, we demonstrate mechanical quantum memory based on a high-stressed silicon nitride (SiN) membrane which is sideband cooled down to its ground state. We investigate an itinerant microwave field captured, stored, and retrieved from a mechanical oscillator based on write and readout pulses that have exponential envelopes. By projecting the retrieval transfer pulse to orthogonal and damped oscillatory functions, we determine two quadrature amplitudes and yield a single point in the quadrature phase space that represents the best estimate of the mechanical resonator. The phase space distribution allows us to distinguish between coherent and thermal components and their evolution as a function of the storage time. Benefitting from the long coherence property of the SiN mechanical oscillator, we demonstrate that such mechanical quantum memory performs attractive functions with an energy decay time of T1= 15.9 s, and acquires less than one quantum noise during the Τcoh = 55.7 ms storage period. These results suggest that high-Q mechanical resonators and long coherence time phonons could be ideal candidates for the construction of microwave quantum memories
Metal Organic Framework Template-Guided Electrochemical Lithography
Authors: Lu Youyou , Zhang Xuan , Zhao Liyan , Mochizuki Kenji , Yang Shikuan
Published: February 2023

The templating method is promising in fabrication of surface nanopatterns. Exploring new functions of the templates besides the masking and the molding function are important to strengthen their manufacturing capability towards complex surface nanopatterns. Here, we employed the metal organic framework (MOF) octahedra assembled monolayer as a template to perform metal electrodeposition and revealed the previously unidentified guiding growth mode capable of growing metallic films exactly underneath the MOF octahedra. The fast ion transport within the nanochannels of the MOF octahedral accounted for the guiding growth mode proven by the experimental measurements and the molecular dynamics simulations. The MOF template could be repeatedly used to create the same metallic surface nanopatterns on different substrates. The recyclability and the feasibility to create fine MOF nanopatterns using sophisticated lithographic methods endow the MOF’s guiding growth mode with great potentials in creating complex metallic surface nanopatterns at a low cost.
Structure-evolution-designed amorphous oxides for dielectric energy storage
Authors: Yu Yahui , Zhang Qing , Xu Zhiyu , Zheng Weijie , Xu Jibo , Xi Zhongnan , Zhu Lin , Ding Chunyan , Cao Yanqiang , Zheng Chunyan , Qin Yalin , Li Shandong , Li Ai-Dong , Wu Di , Rabe Karin , Liu Xiaohui , Wen Zheng
Published: February 2023

Dielectric capacitors are fundamental for electric power systems due to the fast charging/discharging rate and high-power density.[1,2] Recently, rapidly increased demands of miniaturization and integration continuously challenge energy storage density of dielectric capacitors, especially for that could be compatible with the complementary metal-oxide-semiconductor (CMOS) technology, for developing energy-autonomous systems and implantable/wearable electronics, where high-κ capacitors become increasingly desirable in the next-generation applications.[3-5] However, their recoverable energy storage densities (Urec) are low in emerging capacitive energy storage materials. Here, by structure evolution between fluorite HfO2 and perovskite hafnate who have similar metal sublattices, we create an amorphous hafnium-based oxide that exhibits a giant Urec of ~155 J/cm3 with an efficiency (η) of 87%, which is record-high in high-κ materials and state-of-the-art in dielectric energy storage. The improved energy density is owing to the strong structure disordering in both short and long ranges induced by oxygen instability in between the two energetically-favorable crystalline forms. As a result, the carrier avalanche is impeded and an ultrahigh breakdown strength (Eb) up to 12 MV/cm is achieved, which, accompanying with a large permittivity (εr), remarkably enhances the dielectric energy storage. Our study provides a new and widely applicable playground for designing high-performance dielectric energy storage with the strategy exploring the boundary among different categories of materials.
Patterns of Violence and Mental Health Outcomes Before and During the COVID-19 Pandemic: Characterizing Vulnerability in Sexual and Gender Minority College Students
Authors: Deng Wisteria , Xie Hui , Creighton Mackenzie , Lin Yezhe
Published: February 2023

Background. Lockdown measures and remote learning during the COVID-19 pandemic have had a large impact on the physical and mental health of college students, especially those with minority identities. Sexual and gender minority (SGM) students are especially at risk for sexual violence and subsequent adverse mental health outcomes on campus. It is worth examining how pandemic-related changes on campus may pose differential types of threat to SGM college students. The present study aimed to juxtapose patterns of violence among college students before and during the pandemic, and explore the risks and consequences of violence/assaults among minority groups.
Methods. The study utilizes the 2018-2019 and 2020-2021 Healthy Minds Study (HMS) datasets. The HMS is a web-based survey data focuses on mental health, health behavior, campus climates and related issues among a nationally representative sample of undergraduate and graduate students from 60 U.S. campuses.
Results. Results demonstrated that violence committed by strangers/acquaintances decreased during the pandemic for all college students, while sexual assaults by ex or current partners remained unchanged.Further, SGM students experienced increased sexual violence and adverse mental health outcomes during the pandemic.
Limitations. While the two cohorts in comparison were collected before and during the pandemic, they were not based on the same sample. Future research should collect longitudinal data to understand the impacts of sexual violence over time.
Conclusions. The present study serves as a starting point to understand the sexual violence and heightened mental health risk experienced by sexual and gender minority college students.