bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemical Bowel Preparation Exerts an Independent Preventive Effect Against Surgical Site Infection Following Elective Laparoscopic Colorectal Surgery
Authors: Ichimura Kentaro , Imaizumi Ken , Kasajima Hiroyuki , Sato Aya , Sato Kentaro , Yamana Daisuke , Tsuruga Yosuke , Umehara Minoru , Kurushima Michihiro , Nakanishi Kazuaki 
Published: August 2022

Abstract
Purpose: We investigated the clinical value of mechanical and chemical bowel preparations (MBP, CBP) for preventing surgical site infection (SSI) in patients undergoing elective laparoscopic colorectal surgery. Methods: This retrospective cohort study included 475 patients who underwent elective laparoscopic colorectal surgery between January 2018 and March 2022. CBP was introduced in January 2021. CBP included kanamycin (1 g) and metronidazole (1 g) two times a day, the day before surgery. In some cases, MBP was omitted in patients who planned to undergo right-sided colectomy, those with tumor obstruction, and those with poor general condition, depending on the physician’s judgment. The endpoints were primarily the overall incidence of SSI, and secondarily incisional SSI, organ-space SSI, culture from the surgical site, and postoperative hospital stay. Results: In total, 136 patients underwent CBP. MBP was omitted in 53 patients. Overall, SSI occurred in 80 patients (16.8%), including 61 cases of incisional SSI (12.8%) and 36 cases of organ-space SSI (7.6%). Multivariate logistic regression revealed that CBP exerted an independent preventive effect on overall and incisional SSI, whereas MBP did not. Levels of Bacteroides species at the surgical site were significantly lower in the CBP group than in the non-CBP group. Postoperative hospital stay was significantly longer in the incisional SSI group than in non-SSI group and was significantly longer in the organ-space SSI group than in the other groups.Conclusion: CBP, but not MBP, exerts an independent preventive effect on SSI, especially incisional SSI, in patients undergoing elective laparoscopic colorectal surgery.
Long-term outcomes of laparoscopic versus open colectomy for pathological T4 and/or N2 colon cancer patients: multicenter study using propensity-score matched analysis
Authors: Hashimoto Shintaro , Tominaga Tetsuro , Nonaka Takashi , Shiraishi Toshio , To Kazuo , Takeshita Hiroaki , Fukuoka Hidetoshi , Araki Masato , Tanaka Kenji , Sawai Terumitsu , Nagayasu Takeshi 
Published: August 2022

Abstract
Purpose
Although the safety and comparable long-term outcomes after laparoscopic surgery (LAP) for advanced colon cancer versus open surgery (OP) were previously reported, the indications for highly advanced colon cancer are controversial. We aimed to assess long-term outcomes after LAP versus OP for pathological T4 (pT4) and/or N2 (pN2) colon cancer.
Methods
We retrospectively reviewed 255 primary tumor resections for pT4 and/or pN2 colon cancer performed from 2015 to 2020 at six hospitals, divided into LAP (n = 204) and OP groups (n = 51). After propensity score matching to minimize selection bias, 42 matched patients per group were assessed.
Results
Before matching, the rate of males (53.9% vs 37.3%, p = 0.042), left sided colon cancer (53.9% vs 37.3%, p = 0.042), D3 lymph node dissection (90.7% vs 68.6%, p < 0.001) and BMI (kg/m2) (22.3 vs 21.8, p = 0.039) were significantly greater in the LAP group. The rate of pT4 (60.3% vs 82.4%, p = 0.003) was lower and pN2 was higher (57.4% vs 37.3%. p = 0.012) in the LAP group. After matching, preoperative characteristics and pathologic status were equivalent between the groups. The LAP and OP groups showed comparable 5-year overall survival (OS) (75.3% vs 60.4%, p = 0.448) and 5-year recurrence-free survival (RFS) (55.5% vs 57.4%, p = 0.411). In the patients with pT4, OS (67.3% vs 76.4%, p = 0.927) and RFS (46.1% vs 62.8%, p = 0.971) were comparable. In the patients with pN2, OS (77.7% vs 51.6%, p = 0.545) and RFS (57.6% vs 43.1%, p = 0.204) were also comparable.
Conclusions
LAP for pT4 and/or pN2 colon cancer showed comparable long-term outcomes compared with OP. LAP was an acceptable surgical approach in this cohort.
OAM-GANN: Online Adaptive Memory based Genetically optimized Artificial Neural Network for PUEA Detection in CRN Applications
Authors: V Noel Jeygar Robert 
Published: August 2022

Abstract
Cognitive Radio Networks (CRNs) allows opportunistic usage of spectrums owned by licensed users or primary users (PUs). The unlicensed users or secondary users (SUs) that use the spectrum rely opportunistically on spectrum sensing to determine the presence of PU signal. Unfortunately, this attribute opens the door for attacks such as the as the Primary User Emulation Attack (PUEA). This attack happens when an attacker emulates a PU signal. The intention of the attacker might be to grab the vacant channels for its data transmission or entirely disrupt the working of the CRN. Hence it is necessary to combat the consequences of PUEA effectively. Artificial Intelligence (AI) has shown its excellence in various applications including the detection of PUEA. To further enhance the security of the CRN, this research work proposes a novel classification framework called Online Adaptive Memory based Genetically optimized Artificial Neural Network (OAM-GANN) which introduces adaptive online learning of network parameters to identify the presence of PUEA. The proposed OAM-GANN involves Computational Intelligence (CI) algorithm called Memory based Genetic Algorithm (MGA) to optimally tune the hyperparameters of the developed ANN. The advantages of online adaptive training and optimal hyperparameter tuning of the AI model, result in improved security to the network and the data being transmitted in the CRN. The performance of the proposed attack detection model is evaluated in terms of accuracy, sensitivity, specificity, error rate, and detection probability. In addition, the performance of the proposed secure CRN is evaluated in terms of throughput and packet delivery ratio.
Ensured Lifespan of IoT in 5G Depends on Metaheuristic Algorithm-Genetic Algorithm
Authors: Qamar Shamimul 
Published: August 2022

Abstract
Mobile Cellular networks are developing to the period of 5G, for empowering elegant and inventive resources of IoT, the new 5 th generation radio (NR), lifelong evolution like (LTE-A) high tech are intended. Although, the current LTE-A master entente namely group paging technique is still steadily influenced concerning person-to-person communication following the varying characteristics of an extensive variety of Internet of things devices. From way back, utmost Internet of Things are operated with the help of battery which the rate of power consumption is the deciding factor of their battery lifetime, therefore energy-efficient transferring protocols of data are of outstanding importance future generation Internet of Things networks. One of the examples in improving the energy efficiency of Internet of things networks is group paging. Yet, the approach of grouping for the Internet of things mechanism is quite not much an important topic to discuss. Hence, this paper suggested an inventive different criterion transmutative optimization, specifically, genetic algorithm. The output attained from simulation confirms that our suggested technique can appreciably improve the energy efficiency of Internet of things gadgets. The results of the simulation of this suggested algorithm illustrate that it will intersect at the classic solution fast and convince the demand of small node implementation rate and a high rate of coverage, thus extending the lifespan of the network accurately.
To Prolong the life of IoT in the fifth generation utilising a parallelly implemented Multiobjective Algorithm with Mapping Reduce
Authors: Qamar Shamimul 
Published: August 2022

Abstract
Extended dimensions, high speeds, superior reliability, and negligible latency, increased capacity, and better QoS are some of the major objectives or challenges that must be communicated in the near future, i.e., far away 4G. To address these issues, urgent advancements in cellular network architecture are required [7]. The introduction of the fifth generation in 2020 will have an impact on a wide range of technological fields. Smaller delays, faster data transmission, and better connectivity will all be features of 5th generation. The Internet of Things will undergo significant changes. The internet of things (IoT) is a developing technology of internet-connected physical devices with the ability to collect and share large amounts of data. High speeds, maximum connectivity, ultralow latency, and universal coverage will all be available with 5th generation technology. The coverage problem in wireless sensor networks (WSNs) is interpreted by calculating the efficacy of how a web zone is observed with its sensor networks.To address these coverage issues, comprehensive coverage protocols have been devised [6]. Organizations are expected to begin establishing the number of these connected devices after considering all parameters such as increasing transmitted data speed and resolving latency issues.To solve the coverage problem and to extend the lifespan of the Internet of Things they used the parallel genetic algorithm with a huge number of connections. The algorithm should consider both node redundancy and coverage while evaluating the result of the current configuration of effective nodes.
Throughput and Outage Probability-aware Intelligent Swarm-based Multi-hop Selection in Vehicular Network
Authors: Qamar Shamimul 
Published: August 2022

Abstract
Cooperation is an emerging paradigm for improving the spatial differentiations in Vehicular Ad-Hoc Networks (VANET). Cooperative communication systems can improve the performance and spatial diversity equivalent to the multiantenna systems like Multiple-Input Multiple-Output (MIMO) systems. Additionally, these systems are more realistic for the implementation with conventional limited resources and distributed hardware. Hence, many network solutions are motivated through the cooperative communications for boosting VANET efficiency regarding specific network constraints like energy efficiency, network capacity, and outage probability. As several effective studies are discussed about VANETs integrated with cooperative communications, it suffers from some basic problems, which does not explicitly utilize. The main goal of this article is to design & develop an optimization method for selecting the minimum number of multi-hops between source and destination for the cooperative VANET network. The first phase has first time slot, where a signal is transmitted by source to the cooperative nodes (its relays) and to their equivalent destination. The main problem considered here is to optimally select the number of hops or relays that to be adaptable for communication, with the intention of solving the multi-objective function concerning with the target throughput and outage probability. The adoption of new Dimension-based Cat Swarm Optimization (D-CSO) is the main contribution here to optimally select the multi-hops among source and destination. Through the performance evaluation, it is observed that the designed model has achieved network-wide fairness performance and good convergence rate.
Discovering the Optimal Number of Crime Cluster Using Elbow, Silhouette, Gap Statistics, and NbClust Methods
Authors: Sagala Noviyanti T. M. , Gunawan Alexander Agung Santoso 
Published: August 2022

In recent years, crime has been critical to be analyzed and tracked to identify the trends and associations with crime patterns and activities. Generally, the analysis is conducted to discover the area or location where the crime is high or low by using different clustering methods, including k-means clustering. Even though the k-means algorithm is commonly used in clustering techniques because of its simplicity, convergence speed, and high efficiency, finding the optimal number of clusters is difficult. Determining the correct clusters for crime analysis is critical to enhancing current crime resolution rates, avoiding future incidents, spending less time for new officers, and increasing activity quality. To address the problem of estimating the number of clusters in the crime domain without the interference of humans, the research carried out Elbow, Silhouette, Gap Statistics, and NbClust methods on datasets of Major Crime Indicators (MCI) in 2014−2019. Several stages were performed to process the crime datasets: data understanding, data preparation, cluster modelling, and cluster validation. The first two phases were performed in the R Studio environment and the last two stages in Azure Studio. From the experimental result, Elbow, Silhouette, and NbClust methods suggest a similar number of optimum clusters that is two. After validating the result using the average Silhouette method, the research considers two clusters as the best clusters for the dataset. The visualization result of Silhouette method displays the value of 0,73. Then, the observation of the data is well-grouped. It is placed in the correct group.
Regression models for predicting the die-off rate of E. coli in solar water disinfection
Authors: Nwankwo Ekene Jude , Agunwamba Jonah Chukwuemeka , Igwe Samson Ekene , Odenigbo Celestine 
Published: August 2022

Abstract
Solar disinfection (SODIS) is an economical and user-friendly method of water purification mostly applied in the tropical countries. SODIS uses the ultraviolet (UV) and temperature effects of the sun to kill pathogens in drinking water. The objective of the study was to develop a functional relationship between pathogen die-off rate and SODIS treatment conditions, namely daily maximum of 5-h averages of UV intensity , daily maximum water temperature , and water turbidity . Regression analyses/models based on 5-month data revealed that although and can be excellent predictors of pathogen die-off rate, their variable inflation factors (6.75 and 6.57, respectively), which is a measure of dependence between the two variables and adequacy of the estimated regression coefficients, suggest that they cannot be successfully combined in a single least-square regression model. was found to be a better predictor of in SODIS than . Water turbidities in the range of 1–30 NTU had no significant effect on the pathogen die-off rate. The study concluded that regression models/analyses can be successfully employed to explain the day-to-day variability in pathogen die-off rate, predict SODIS applicability, and exposure period in different regions of the world based on UV, water temperature, and water turbidity.
Assessment of household-level adaptation strategies to water stress in southwestern coastal Bangladesh: a counter-factual analysis
Authors: Ahsan Md. Nasif , Khatun Fatema , Islam Md. Sariful , Hossain Md. Sarwar , Mou Benzir Huq , Kumar Pankaj 
Published: August 2022

AbstractDespite the growing emphasis and global initiatives to ensure safe drinking water and sanitation for all (Sustainable Development Goal 6), households in coastal areas are at risk of growing water stress across the globe. However, little is known about households' adaptation strategies to water stress in coastal areas. This study explores the determinants and impacts of adaptation strategies to household-level water stress (both drinking and non-drinking), considering the behaviors of adopters and non-adopters in the southwestern coastal area of Bangladesh. We applied an endogenous switching regression model by analyzing questionnaire survey datasets (n=502) to estimate the effect of adopting adaptation strategies on household-level water stress in four saline-prone coastal sub-districts of Bangladesh. Results reveal six commonly-practiced adaptation strategies: reducing vegetable production, reducing livestock production, paying more to access water, increasing time for water collection, preserving water, and using reservoirs to collect water. Determinants such as migration, support from government and non-government agencies, age, gender, literacy, occupation, income, access to tube wells, and distance from drinking water sources play a significant role in adopting adaptation strategies. Results from the endogenous switching regression model denote that adopting all six adaptation strategies appears to significantly reduce household-level water stress. Through counter-factual analysis, results demonstrate that, on average, households that did not adopt adaptation strategies would have encountered less water stress if they had. Therefore, determinants that stimulate adaptation strategies will indirectly reduce household water stress.
Combination Therapy of Chemotherapy or Radiotherapy and the
Neurokinin-1 Receptor Antagonist Aprepitant: A New Antitumor
Strategy?
Authors: Robinson Prema , Coveñas Rafael , Muñoz Miguel 
Published: August 2022

Background:
Although chemotherapy is predominantly used for cancer treatment,
it can be ineffective and can induce serious side effects and lead to chemoresistance.
It is essential to discover novel drugs that can enhance the antitumor activity and
at the same time, counteract the severe side effects, of chemotherapy. The substance P
(SP)/neurokinin-1 receptor (NK-1R) interaction system is known to play a key role in the
pathogenesis of cancer. Studies with NK-1R antagonists (such as aprepitant) denote that
the NK-1R is a potential target for the treatment of cancer. Aprepitant combined with major
chemotherapeutic drugs has shown the potential to increase antitumor activity and decrease
side effects.

Objective:
Since malignant tumor cancer cells overexpress the NK-1R, this combination
therapy is a promising approach for the treatment of all kinds of cancer. Since aprepitant
shows potential of being a broad-antitumor drug, the repurposing of this NK-1R antagonist
as an antitumor agent is warranted. Studies pertaining to combination therapy of
aprepitant/radiotherapy will also be outlined in this review. The aim of this review is to
provide an update on combinational studies pertaining to chemotherapy/radiotherapy and
NK-1R antagonist in cancer.

Conclusion:
This combination strategy once confirmed, might open the door to a new
era in chemotherapy and radiotherapy with greater antitumor activity and fewer side effects.
This treatment strategy could possibly translate into higher cure rates, better quality
of life and fewer sequelae in cancer patients.
Synthesis, Molecular Docking and ADME Prediction of 1H-indole/5-
substituted Indole Derivatives as Potential Antioxidant and Anti-
Inflammatory Agents
Authors: Singh Rajesh Kumar , Kumari Archana 
Published: August 2022

Background:
Inflammation is a protective biological process, but under extreme conditions,
it can become highly dreadful to the body. Antioxidant and anti-inflammatory agents treat
similar disease conditions as inflammation and oxidative stress commonly follow similar causative
pathways.

Objective:
The goal of this study was to synthesize N-substituted indole derivatives with different
heterocyclic moieties through propyl linker with the aim of getting highly potent anti-inflammatory
and antioxidant agents.

Methods:
Synthesized compounds were analyzed by analytical techniques such as IR, 1H NMR, 13C
NMR spectra, and mass spectrometry. Molecular docking and ADME calculation were employed on
synthesized compounds to estimate their COX-2 enzyme inhibition and drug like properties, respectively.
Antioxidant activity was evaluated by the DPPH assay and the reducing power assay. Selected
derivatives were evaluated for anti-inflammatory activity at an acute (carrageenan-induced paw edema
method) and chronic level (formalin-induced inflammation method) using indomethacin as a
standard drug.

Results:
Herein, twelve indole derivatives (11a-c, 12a-c, 13a-c, and 14a-c) were synthesized.
Among all, compound 12c was found to be the best inhibitor of the COX-2 enzyme as it displayed
good interaction energy. Zero violations of Lipinski's rule were found in the ADME investigation,
confirming the drug-like qualities of synthesized compounds. The compounds 11a and 12c were
found to be the most potent as compared with standard ascorbic acid in antioxidant evaluation. From
the collected results, compounds 12c and 13b were the most potent against acute and chronic inflammation.

Conclusion:
The novel synthetic indole derivatives could act as potent leads for the development of
novel antioxidant and anti-inflammatory agents.
Recent Advances in the Chemistry and Biology of Bakuchiol and its Derivatives: An
Updated Review
Authors: Gupta Nidhi , Sangwan Payare L. , Shankar Ravi , Gupta Sumeet 
Published: August 2022

Abstract:
Bakuchiol is a meroterpene natural product distributed in various plants. It possesses several biological
activities particularly anticancer. A large number of analogs have been prepared by various researchers by targeting
several positions such as phenolic –OH, ethenyl and isopropylidene groups present in the bakuchiol to develop potent
therapeutic agents with improved pharmaceutical properties. The present review describes the isolation, organic synthetic
schemes, chromatographic study, and biological activities of bakuchiol reported till date. Further, the review also
provides an insight into the skin care effects of bakuchiol and structure-activity relationship studies of reported derivatives.
Moreover, the biosynthetic pathway of bakuchiol has also been described. All the articles published on bakuchiol
revealed that bakuchiol and its analogs possess a remarkable potential for the development of potent anticancer and
several other therapeutic agents. The reported synthetic schemes can be utilized for the industrial production of bakuchiol.
Finally, we believe that this review will provide important information to the researchers interested in the chemistry
and biology of Bakuchiol.
Use of Psychotropics in COVID-19: Another Anti-inflammatory
Pathway
Authors: Morillo Jessenia , Morillo Valery , Marquina Maria Angelica , Rojas Milagros , Nava Manuel 
Published: August 2022

Abstract:
The emergence of the novel coronavirus SARS-CoV-2 has significantly impacted
the world's population, disrupting healthcare systems around the globe and leading to human
and material losses. While different vaccines have been approved in record time, there continues
to be a high number of daily new cases, and patients face a wide range of presentations of
the disease, from asymptomatic to potentially fatal. Therefore, the search for therapeutic agents
that can aid in the management and control of the disease has become one of the main goals for
researchers and clinicians. As an inflammatory disease, targets for the treatment of COVID-19
have largely involved the immune system. Inflammation has also been associated with mental
health disorders, and studies have shown the potential involvement of inflammatory pathways
in the pathophysiology of depression. As a consequence, the hypothesis of using antidepressants
and other psychotropics for the treatment of COVID-19 has emerged. In this review, we
aim to summarize the molecular pathways that could be involved as well as the emergent evidence
that has been reported by studies performed since the appearance of SARS-CoV-2 in
2019. While it has been observed that there are potential therapeutic pathways for the use of
antidepressants in the treatment of COVID-19, additional studies are needed to evaluate the
feasibility, safety, and efficacy of psychotropics in this disease.