bluuebunny/crossref_metadata_2025_split huggingface dataset:
A QSAR Study of Peptidyl Vinyl Sulfone Cysteine Protease Inhibitors Using Topomer CoMFA and Molecular Docking
Authors: Lu-Yang W.U. , Yang-Min M.A. , Shan L.E.I. , Tian-Hao Wang , Yi Feng 
Published: January 2021

Background:
Malaria is one of the most important infectious diseases in the world. The
most severe form of malaria in humans is caused by Plasmodium falciparum. Malaria is a worldwide
health problem, with 214 million new cases in 2015 and 438,000 deaths, most of which are in Africa.
Therefore, there is an urgent need for novel, low-toxic, more specific inhibitors to find new antimalarial
agents. A promising target for antimalarial drug design is falcipain-2, a cysteine protease
from P. falciparum that has received considerable attention due to its key role in the life cycle of the
parasite.

Materials and Methods:
Three-dimensional quantitative structure-activity relationship (3D-QSAR)
models of 39 peptidyl vinyl sulfone cysteine protease inhibitors was constructed using Topomer
CoMFA. Topomer Search was employed to virtually screen lead-like compounds in the ZINC database.
Molecular docking was employed to further explore the binding requirements between the ligands
and the receptor protein which included several hydrogen bonds between peptidyl vinyl sulfone
cysteine protease inhibitors and active site residues.

Results:
The non-cross correlation coefficient (r2), the interaction validation coefficient (q2) and the
external validation (r2
pred) were 0.902, 0.685 and 0.763, respectively. The results showed that the
model not only had good estimation stability but also good prediction capability. 22 new molecules
were obtained, whose predicted activity is higher than the template molecules. The results showed
that the Topomer Search technology can be effectively applied to screen and design new peptidyl
vinyl sulfone cysteine protease inhibitors. Molecular docking showed extensive interactions between
peptidyl vinyl sulfone cysteine protease inhibitors and residues of LYS24, ASP21, LYS59, and
ASP17 in the active site.

Conclusion:
: 39 peptidyl vinyl sulfone cysteine protease inhibitors were used in the 3D-QSAR study.
Topomer CoMFA 3D-QSAR method was used to build the model, and the model was well predicted
and statistically validated. The design of potent new inhibitors of cysteine protease can get useful
insights from these results.
An Efficient Light-weight Network for Fast Reconstruction on MR Images
Authors: Zhen Bowen , Zheng Yingjie , Qiu Bensheng 
Published: January 2021

Background:
In recent years, deep learning (DL) algorithms have emerged endlessly
and achieved impressive performance, which makes it possible to accelerate magnetic resonance
(MR) image reconstruction with DL instead of compressed sensing (CS) methods. However, a DLbased
MR image reconstruction method has always suffered from its heavy learning parameters
and poor generalization ability so far. Therefore, an efficient, light-weight network is still in desperate
need of fast MR image reconstruction.

Methods:
We propose an efficient and light-weight MR reconstruction network (named RecNet)
that uses a Convolutional Neural Network (CNN) to fast reconstruct high-quality MR images. Specifically,
the network is composed of cascade modules, and each cascade module is further divided
into feature extraction blocks and a data consistency layer. The feature extraction block can not only
effectively extract the features of MR images, but also do not introduce too many parameters for
the whole network. To stabilize the training procedure, the correction information of image frequency
is adopted in the data consistency (DC) layer.

Results:
We have evaluated RecNet on a public dataset and the results show that the image quality
reconstructed by RecNet is the best on the peak signal-to-noise ratio (PSNR) and structural similarity
index (SSIM) evaluation standards. In addition, the pre-trained RecNet can also reconstruct high-
-quality MR images on an unseen dataset.

Conclusion:
The results demonstrate that the RecNet has superior reconstruction ability in various
metrics than comparative methods. The RecNet can quickly generate high-quality MR images in
fewer parameters. Furthermore, the RecNet has an excellent generalization ability on pathological
images and different sampling rates data.
The Correlation Between the Autotaxin Enzyme and Pruritus in Egyptian Patients Suffering from Chronic Liver Disease
Authors: Asal Fathia , Ziada Dina , Wageh Ayman , El-Kohy Mohammed , Hawash Nehad , Abd-Elsalam Sherief , Badawi Rehab 
Published: January 2021

Background & Aims:
Pruritus associated with liver diseases confines daily activities and
causes sleep deprivation in patients with chronic liver diseases. Autotoxin enzyme (ATX) was
found to be higher in sera of patients with intrahepatic cholestasis and it was found to be associated
with the intensity of itching. The aim of this study was to assess the correlation between the autotaxin
enzyme and pruritus in Egyptian patients suffering from chronic liver disease (CLD).

Methods:
This cross-sectional study was carried on a total number of 80 patients with chronic liver
disease divided into four groups: Group A and B included cirrhotic patients suffering from pruritis
with and without cholestasis, while group C and D included patients without pruritis with or without
cholestasis and group E included 17 healthy controls. They were subjected to measurement of
serum autotoxin concentration by ELISA in addition to routine investigations including liver function
tests: Total and direct bilirubin, ALT, AST, Alkaline phosphatase, Gama- glutamyl transferase,
and serum albumin.

Results:
There was a significant increase in autotaxin in the four groups included chronic liver disease patients (P value
<0.001*) compared to control group (group E). Autotoxin level was the only marker which had a significant increase in
pruritus groups (groups A & B) compared to non-pruritus groups (groups C & D) with cut off value ≥ 32.

Conclusion:
Serum autotaxin level was elevated in patients with chronic liver diseases with pruritus.
Autotaxin enzyme may play a key role in the induction of hepatogenic pruritus. So, autotaxin
enzyme inhibitors and lysophosphatidic acid (LPA) receptor blockers could be a future line of treatment
of hepatogenic pruritus.
Secure Multi-objective Hybrid Routing Protocol For Wireless Sensor Network
Authors: Kaushik Ruchi , Singh Vijander , Kumari Rajani 
Published: January 2021

Background:
Wireless sensor networks play a significant role in network technologies. It is difficult
to determine an optimal route that satisfies the requirements of wireless sensor networks. Energy-
aware and trust-aware routing protocols play a critical role in the security of wireless sensor
networks. SRPMA routing protocols have limited parameters and functions. The ant colony algorithm
is specifically designed to find the roots in which convergence is limited.

Objective:
This paper proposed an improved multi-objective trust-energy aware hybrid routing protocol
using a hybrid grey wolf genetic algorithm (I-MTERP-GWOGA) to achieve quality service
by optimizing network security and reducing energy consumption in wireless sensor networks.

Methods:
Energy-aware function calculated by the radio energy dissipation model ensures if the
nodes involved in the route are capable of transmitting the data packets successfully or not. The
load function directly impacts the delay of the transmission of data packets.

Results:
I-MTERP-GWOGA algorithm shows better simulation results than secure routing protocol
based on multi-objective ant-colony (SRPMA) and improved ant colony optimization based security
routing protocol (IASR) algorithms using MATLAB 2019a.

Conclusion:
The proposed algorithm improves performance against malicious nodes using five
network performance criteria; packet delivery ratio, packet loss rate, average energy consumption,
and end to end delay.
Using Double DQN and Sensor Information for Autonomous Driving
Authors: Raghavan Ramesh , Verma Dinesh Chander , Bansal Tarun 
Published: January 2021

Background:
In most of the research the autonomous driving problem is either solved with policy gradients or
DQN. In this paper, we have tried to eliminate the problem of policy gradients which is high variance and an
overestimation of values in DQN. We have used DDQN as it has low variance, and it solves the problem of
overestimation in DQN.

Aim:
The main aim of this paper is to propose a framework for an autonomous driving model that takes in raw sensor
information as input data and predicts actions as output from the model which could then be used for simulating the car.

Objective:
The main objective of this paper is to use DDQN and Discretization technique to solve the autonomous driving
problem and get better results even with a continuous action space.

Methods:
To solve the bridge between self-driving cars and reinforcement learning we have used Double Deep QNetworks as this could help to prevent the overestimation of values by decoupling the selection from the evaluation. Also,
to solve the problem of continuous action space we have used the discretization technique in which variables are grouped
into bins and each bin is assigned a value in such a way that the relationship between the bins is preserved.

Result:
The experimental results showed improved performance of the agent. The agent was tested for different conditions
like curve roads and traffic, which showed the agent can drive at different conditions as well. We have also illustrated how
DDQN performed well over policy gradients just by adding a simple discretization technique to make the action space
discrete and overcoming the issue of overestimation of q-values.

Conclusion:
We design the gym environment and reward function for DDQN to work. We have also used CARLA as a
virtual simulator for training purposes. Finally, we have demonstrated that our agent was able to perform well in different
cases and conditions. As a reminder note, we can improve our agent to also work for following traffic light rules and other
road safety measures.
A Comprehensive Review on Recently Detected Herbal Phytoactives
Having Anti-Diabetic Potential for Various Diabetes-Related Complications
Authors: Wal Pranay , Wal Ankita , Pal Rashmi Saxena , Singh Priya 
Published: January 2021

Background:
Diabetes is a metabolic, endocrine disorder which is featured by hyperglycemia and glucose intolerance, primarily due to beta cell destruction, with Insulin Resistance playing a secondary role. It is treated with the help of
many chemical based drugs as well as natural derivatives.

Objective:
There is urgent need to develop new efficacious, cheaper and more available drugs to face this growing public
health challenge. Many anti-diabetic drugs are often often associated with many adverse effects.

Materials & Methods:
Literature was reviewed in a narrative manner in order to pertain the information about active phytoactives present in the different plants. Anti-diabetic drugs are often loaded with side effects; therefore, review is being
done for the selection of effective natural therapeutic moieties with less or no adverse effects.

Results:
In this review article, we described the detailed review of recently detected bioactive compounds present in different natural substances; which can be used effectively for diabetes related adversities.

Conclusion:
Natural products based bioactive molecules have been proven to improve insulin resistance and other related
complications through suppression of inflammatory signaling pathways.
Vertical Garden Sebagai Solusi Degradasi Ruang Terbuka Hijau dan Edukasi Santri Wahid Hasyim Yogyakarta
Authors: Indriani Hesti , Rafida Aulia Nisa , Khasanah Miftakhul , Handziko Rio Christy 
Published: January 2021

Jumlah penduduk perkotaan yang terus meningkat memberikan dampak tingginya tekanan terhadap pemanfaatan ruangkota, terutama ruang terbuka hijau sebagai ruang terbuka publik yang berpotensi menjadi ruang permukiman. Meningkatnya pembangunan akan mengurangi ruang terbuka hijau yang ada. Pondok Pesantren Wahid Hasyim Yogyakarta merupakan salah satu pondok pesantren yang ada di pusat kota Yogyakarta yang memiliki lembaga pendidikan dari TK, MTs, MA, dan SMA. Pembangunan disanaterus meningkat seiring dengan meningkatnya siswa yang ada. Oleh karena itu, ruang terbuka hijau menjadi semakin berkurang.Vertical Garden adalah sebuah solusi permasalahan degradasi ruang terbuka hijau di Pondok Pesantren Wahid Hasyim yang menggunakan pendekatan keruangan dengan memaksimalkan lahan kota yang sempit. Penelitian ini menggunakan metode kombinasi penelitian lapangan dan analisis data sekunder.Verical Garden merupakan konsep taman tegak yang menjadikan ruang tanam lebih besar dibanding taman konvensional, sehingga dapat menambah ruang terbuka hijau di Pondok Pesantren Wahid Hasyim Yogyakarta. Kata Kunci :Vertical Garden, Ruang Terbuka Hijau, Lahan Sempit, Yogyakarta.
PKM Pengolahan Air Gambut di Desa Kasamukal dan Desa Rawa Makmur, Kecamatan Bonai Darussalam, Kabupaten Rokan Hulu, Riau
Authors: Febriani Yeza , Meirina Eti , Brahmana Brahmana , Aprizal Aprizal , Saleh Arif Rahman 
Published: January 2021

Air gambut merupakan jenis air yang banyak tersedia di sekitar kawasan hutan lahan rawa gambut. Air ini perlu pengolahan terlebih dahulu sebelum siap untuk dikonsumsi dikarenakan tidak memenuhi persyaratan standar kualitas air bersih layak konsumsi. Beberapa desa yang terletak di Kecamatan Bonai Darussalam Kabupaten Rokan Hulu masih menemukan kesulitan dalam memperoleh air bersih dikarenakan daerah ini merupakan daerah air gambut. Untuk mengolah air gambut dibutuhkan beberapa tahapan mulai dari netralisasi, aerasi, koogulasi-flokulasi, dan filtrasi. Melalui kegiatan pengabdian masyarakat ini telah dibangun sebuah produk berupa sistem penyaringan air gambut menggunakan teknologi sederhana dengan kapasitas penyaringan 500 liter/jam yang terdiri dari beberapa bagian yaitu Tangki Air Baku, Sistem Aerasi, Sistem Pemipaan dan Sistem Penyaring (filter). Media yang digunakan adalah zeolit, pasir silika dan karbon aktif. Seluruh media penyaringan ditempatkan pada 3 buah tabung FRV. Hasil pengujian sampel air hasil penyaringan menunjukkan bahwa teknologi sederhana penyaringan air gambut menjadi air bersih telah bekerja dengan baik dan sesuai dengan PERMENKES No :416/Menkes/PER/IX/1990. Kata kunci: air gambut, teknologi sederhana, penyaringan
Development of a Web-Based Intervention Course to Promote Students’ Well-Being and Studying in Universities: Protocol for an Experimental Study Design
Authors: Asikainen Henna , Katajavuori Nina 
Published: January 2021

Background
The decline in the well-being among university students well as increasing dropouts has become a serious issue in universities around the world. Thus, effective ways to support students’ well-being and their ability to study are highly needed.

Objective
The purpose of this study was to build an intervention course for university students, which promotes both students’ well-being as well as their learning and study skills, and to describe the experimental study design that explores the effects of this intervention course.

Methods
Research has shown that psychological flexibility has a great effect on the well-being as well as the study skills of students pursuing higher education. The basis of our intervention course was to promote psychological flexibility and students’ study skills with the help of peer support and reflection.

Results
This course was offered as a voluntary course to all the students at the University of Helsinki twice during the academic year 2020-2021. The first course was from October to December and the second course was from January to March. This course was advertised in fall 2020 through social media and by different student organizations and program leaders at different faculties of the University of Helsinki. As of October 2020, we enrolled 566 students comprising 310 students for the course in fall 2020 and 256 students for the course in spring 2021. Of the 256 students who enrolled in the second course, 170 students voluntarily participated in this study and they answered the questionnaires, including all the measures, simultaneously with the participants in the first group and thus served as the control group. The effect of this course will be measured with multiple data, including questionnaire data, reflective journals, and physiological data of well-being with a longitudinal experimental design. This research very strictly follows the ethical guidelines drawn up by the Finnish National Board on Research Integrity. We expect to publish the results of this study in fall 2021 at the latest.

Conclusions
We argue that a web-based, 8-week intervention course, which promotes both student well-being and their study skills, is a good way to support students pursuing higher education, and both aspects should be considered when supporting university students.

International Registered Report Identifier (IRRID)
DERR1-10.2196/23613
Novel Analgesic Index for Postoperative Pain Assessment Based on a Photoplethysmographic Spectrogram and Convolutional Neural Network: Observational Study
Authors: Choi Byung-Moon , Yim Ji Yeon , Shin Hangsik , Noh Gyujeong 
Published: January 2021

Background
Although commercially available analgesic indices based on biosignal processing have been used to quantify nociception during general anesthesia, their performance is low in conscious patients. Therefore, there is a need to develop a new analgesic index with improved performance to quantify postoperative pain in conscious patients.

Objective
This study aimed to develop a new analgesic index using photoplethysmogram (PPG) spectrograms and a convolutional neural network (CNN) to objectively assess pain in conscious patients.

Methods
PPGs were obtained from a group of surgical patients for 6 minutes both in the absence (preoperatively) and in the presence (postoperatively) of pain. Then, the PPG data of the latter 5 minutes were used for analysis. Based on the PPGs and a CNN, we developed a spectrogram–CNN index for pain assessment. The area under the curve (AUC) of the receiver-operating characteristic curve was measured to evaluate the performance of the 2 indices.

Results
PPGs from 100 patients were used to develop the spectrogram–CNN index. When there was pain, the mean (95% CI) spectrogram–CNN index value increased significantly—baseline: 28.5 (24.2-30.7) versus recovery area: 65.7 (60.5-68.3); P<.01. The AUC and balanced accuracy were 0.76 and 71.4%, respectively. The spectrogram–CNN index cutoff value for detecting pain was 48, with a sensitivity of 68.3% and specificity of 73.8%.

Conclusions
Although there were limitations to the study design, we confirmed that the spectrogram–CNN index can efficiently detect postoperative pain in conscious patients. Further studies are required to assess the spectrogram–CNN index’s feasibility and prevent overfitting to various populations, including patients under general anesthesia.

Trial Registration
Clinical Research Information Service KCT0002080; https://cris.nih.go.kr/cris/search/search_result_st01.jsp?seq=6638
Correlations Between Facial Expressivity and Apathy in Elderly People With Neurocognitive Disorders: Exploratory Study
Authors: Zeghari Radia , König Alexandra , Guerchouche Rachid , Sharma Garima , Joshi Jyoti , Fabre Roxane , Robert Philippe , Manera Valeria 
Published: January 2021

Background
Neurocognitive disorders are often accompanied by behavioral symptoms such as anxiety, depression, and/or apathy. These symptoms can occur very early in the disease progression and are often difficult to detect and quantify in nonspecialized clinical settings.

Objective
We focus in this study on apathy, one of the most common and debilitating neuropsychiatric symptoms in neurocognitive disorders. Specifically, we investigated whether facial expressivity extracted through computer vision software correlates with the severity of apathy symptoms in elderly subjects with neurocognitive disorders.

Methods
A total of 63 subjects (38 females and 25 males) with neurocognitive disorder participated in the study. Apathy was assessed using the Apathy Inventory (AI), a scale comprising 3 domains of apathy: loss of interest, loss of initiation, and emotional blunting. The higher the scale score, the more severe the apathy symptoms. Participants were asked to recall a positive and a negative event of their life, while their voice and face were recorded using a tablet device. Action units (AUs), which are basic facial movements, were extracted using OpenFace 2.0. A total of 17 AUs (intensity and presence) for each frame of the video were extracted in both positive and negative storytelling. Average intensity and frequency of AU activation were calculated for each participant in each video. Partial correlations (controlling for the level of depression and cognitive impairment) were performed between these indexes and AI subscales.

Results
Results showed that AU intensity and frequency were negatively correlated with apathy scale scores, in particular with the emotional blunting component. The more severe the apathy symptoms, the less expressivity in specific emotional and nonemotional AUs was displayed from participants while recalling an emotional event. Different AUs showed significant correlations depending on the sex of the participant and the task’s valence (positive vs negative story), suggesting the importance of assessing male and female participants independently.

Conclusions
Our study suggests the interest of employing computer vision-based facial analysis to quantify facial expressivity and assess the severity of apathy symptoms in subjects with neurocognitive disorders. This may represent a useful tool for a preliminary apathy assessment in nonspecialized settings and could be used to complement classical clinical scales. Future studies including larger samples should confirm the clinical relevance of this kind of instrument.