bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimentally implementing the step-dependent discrete-time quantum walk on quantum computers
Authors: Khan Luqman , Zaman Anwar , Ahmad Rashid , Khan Sajid
Published: December 2022

The discrete-time quantum walk (DTQW) with step-dependent (SD) scattering operator is implemented on quantum computer. The probabilities of different states, with their respective fidelities, are calculated. This is done by generalizing the coin with a rotation gate using the quantum gate model. The CNOT gates in the shift operator are replaced with the alternative to CNOT gates Rx( π). They are applied on a quantum device and a quantum simulator (QS). The fidelities varied around 50% and the probability distribution of SD-DTQW for the angle π/4 spread symmetrically, while the step-independent DTQW (SI-DTQW) tended to peak at one side. The symmetric probability distribution of SD-DTQW can help in better control of the walk on QS. In the case of angle π/2, the SI-DTQW spread equally across the states with four peaks, while the SD-DTQW spread with two peaks to one side.
Fission-stability of high-K states in superheavy nuclei
Authors: Khuyagbaatar J.
Published: December 2022

Fission is the one of the primary radioactive decay modes for the heaviest nuclei and ultimately determines the existence of the heaviest elements on a macroscopic time scale, e.g., $$\ge 10^{-14}$$

≥

10

-
14

 s. The present experimental data on the decay properties of the heaviest nuclei with proton numbers 102–118 and/or of neutron numbers up to 177 show that fission occurs occasionally. This confirms that shell structure plays an essential role for their stability against fission. The shell effect on fission manifests in both collective and single-particle ways, which can experimentally be studied in decays of even–even, odd-A and odd–odd nuclei. At the same time, high-K states formed in couplings of quasiparticles are also known to be stable against fission. However, detailed knowledge and theoretical descriptions on a retardation effect/strength of high-K quantum number on fission are still scarce. In the present work, fission from high-K states are discussed and described within the semi-empirical approach. Fission half-lives are calculated for various high-K states, which have been theoretically predicted to exist in Fm-Rf (Z = 100–104) and Hs-Ds (Z = 108–112). The results are found to be in line with the available experimental findings, and also leading to different intriguing predictions, e.g., high-K states in superheavy nuclei tend to be more stable against fission compared to their ground states.
Study of Noether symmetry analysis for a cosmological model with variable G and $$\Lambda $$ gravity theory
Authors: Bhaumik Roshni , Dutta Sourav , Chakraborty Subenoy
Published: December 2022

In this present model we have discussed about the solution of the matter-dominated cosmological equations using the expression of $$\Lambda =\Lambda (G)$$

Λ
=
Λ
(
G
)

. Using Noether symmetry analysis we have analyzed both the classical and quantum cosmology. We have made a suitable point transformation in order to make one variable cyclic. As a result the evolution equations become simpler to solve. Wheeler–DeWitt (WD) equation has been constructed for this cosmological model and using conserved charge we have found the solution of WD equation. Finally the solutions have been analyzed in the cosmological point of view.
A reconstruction method for anisotropic universes in unimodular F(R)-gravity
Authors: Costantini A. , Elizalde E.
Published: December 2022

An extension of unimodular Einsteinian gravity in the context of F(R) gravities is used to construct a class of anisotropic evolution scenarios. In unimodular GR the determinant of the metric is constrained to be a fixed number or a function. However, the metric of a generic anisotropic universe is not compatible with the unimodular constraint, so that a redefinition of the metric, to properly take into account the constraint, need be performed. The unimodular constraint is imposed on F(R) gravity in the Jordan frame by means of a Lagrangian multiplier, to get the equations of motion. The resulting equations can be viewed as a reconstruction method, which allows to determine what function of the Ricci scalar can realize the desired evolution. For the sake of clarity, some characteristic examples are invoked to show how this reconstruction method works explicitly. The de Sitter spacetime here considered, in the context of unimodular F(R) gravity, is suitable to describe both the early- and late-time epochs of the universe history.
Competitive Algorithms for Generalized
k
-Server in Uniform Metrics
Authors: Bansal Nikhil , Eliáš Marek , Koumoutsos Grigorios , Nederlof Jesper
Published: December 2022

The generalized
k
-server problem is a far-reaching extension of the
k
-server problem with several applications. Here, each server

s
i

lies in its own metric space

M
i

. A request is a
k
-tuple
r
= (
r
1
,
r
2
,… ,

r
k

, which is served by moving some server

s
i

to the point

r
i
∈ M
i

, and the goal is to minimize the total distance traveled by the servers. Despite much work, no
f
(
k
)-competitive algorithm is known for the problem for
k
> 2 servers, even for special cases such as uniform metrics and lines.

Here, we consider the problem in uniform metrics and give the first
f
(
k
)-competitive algorithms for general
k
. In particular, we obtain deterministic and randomized algorithms with competitive ratio
k
· 2

k

and
O
(
k
3
log
k
), respectively. Our deterministic bound is based on a novel application of the polynomial method to online algorithms, and essentially matches the long-known lower bound of 2

k

-1. We also give a 2

2

O(k)

-competitive deterministic algorithm for weighted uniform metrics, which also essentially matches the recent doubly exponential lower bound for the problem.
PTAS for Sparse General-valued CSPs
Authors: Mezei Balázs F. , Wrochna Marcin , Živný stanislav
Published: December 2022

We study polynomial-time approximation schemes (PTASes) for constraint satisfaction problems (CSPs) such as Maximum Independent Set or Minimum Vertex Cover on sparse graph classes.

Baker’s approach gives a PTAS on planar graphs, excluded-minor classes, and beyond. For Max-CSPs, and even more generally, maximisation finite-valued CSPs (where constraints are arbitrary non-negative functions), Romero, Wrochna, and Živný [SODA’21] showed that the Sherali-Adams LP relaxation gives a simple PTAS for all fractionally-treewidth-fragile classes, which is the most general “sparsity” condition for which a PTAS is known. We extend these results to general-valued CSPs, which include “crisp” (or “strict”) constraints that have to be satisfied by every feasible assignment. The only condition on the crisp constraints is that their domain contains an element that is at least as feasible as all the others (but possibly less valuable).

For minimisation general-valued CSPs with crisp constraints, we present a PTAS for all
Baker
graph classes—a definition by Dvořák [SODA’20] that encompasses all classes where Baker’s technique is known to work, except for fractionally-treewidth-fragile classes. While this is standard for problems satisfying a certain monotonicity condition on crisp constraints, we show this can be relaxed to
diagonalisability
—a property of relational structures connected to logics, statistical physics, and random CSPs.
EASYR:

E

nergy-Efficient

A

daptive

Sy

stem

R

econfiguration for Dynamic Deadlines in Autonomous Driving on Multicore Processors
Authors: Yi Saehanseul , Kim Tae-Wook , Kim Jong-Chan , Dutt Nikil
Published: December 2022

The increasing computing demands of autonomous driving applications have driven the adoption of multicore processors in real-time systems, which in turn renders energy optimizations critical for reducing battery capacity and vehicle weight. A typical energy optimization method targeting traditional real-time systems finds a critical speed under a static deadline, resulting in conservative energy savings that are unable to exploit dynamic changes in the system and environment. We capture emerging dynamic deadlines arising from the vehicle’s change in velocity and driving context for an additional energy optimization opportunity. In this article, we extend the preliminary work for uniprocessors [
66
] to multicore processors, which introduces several challenges. We use the state-of-the-art real-time gang scheduling [
5
] to mitigate some of the challenges. However, it entails an NP-hard combinatorial problem in that tasks need to be grouped into gangs of tasks, gang formation, which could significantly affect the energy saving result. As such, we present EASYR, an adaptive system optimization and reconfiguration approach that generates gangs of tasks from a given directed acyclic graph for multicore processors and dynamically adapts the scheduling parameters and processor speeds to satisfy dynamic deadlines while consuming as little energy as possible. The timing constraints are also satisfied between system reconfigurations through our proposed safe mode change protocol. Our extensive experiments with randomly generated task graphs show that our gang formation heuristic performs 32% better than the state-of-the-art one. Using an autonomous driving task set from Bosch and real-world driving data, our experiments show that EASYR achieves energy reductions of up to 30.3% on average in typical driving scenarios compared with a conventional energy optimization method with the current state-of-the-art gang formation heuristic in real-time systems, demonstrating great potential for dynamic energy optimization gains by exploiting dynamic deadlines.
Heterogeneous Information Crossing on Graphs for Session-Based Recommender Systems
Authors: Zheng Xiaolin , Wu Rui , Han Zhongxuan , Chen Chaochao , Chen Linxun , Han Bing
Published: December 2022

Recommender systems are fundamental information filtering techniques to recommend content or items that meet users’ personalities and potential needs. As a crucial solution to address the difficulty of user identification and unavailability of historical information, session-based recommender systems provide recommendation services that only rely on users’ behaviors in the current session. However, most existing studies are not well-designed for modeling heterogeneous user behaviors and capturing the relationships between them in practical scenarios. To fill this gap, in this article, we propose a novel graph-based method, namely
H
eterogeneous
I
nformation
C
rossing on
G
raphs (HICG). HICG utilizes multiple types of user behaviors in the sessions to construct heterogeneous graphs, and captures users’ current interests with their long-term preferences by effectively crossing the heterogeneous information on the graphs. In addition, we also propose an enhanced version, named HICG-CL, which incorporates the contrastive learning (CL) technique to enhance item representation ability. By utilizing the item co-occurrence relationships across different sessions, HICG-CL improves the recommendation performance of HICG. We conduct extensive experiments on three real-world recommendation datasets, and the results verify that (i) HICG achieves state-of-the-art performance by utilizing multiple types of behaviors on the heterogeneous graph. (ii) HICG-CL further significantly improves the recommendation performance of HICG by the proposed contrastive learning module.
A LASSO-Based Prediction Model for Child Influenza Epidemics: A Case Study of Shanghai, China
Authors: Zhu Jin , Xu Yu , Yu Guangjun , Gao Jie , Liu Yuan , Cheng Dayu , Song Ci , Chen Jie , Pei Tao
Published: December 2022

Child influenza is an acute infectious disease that places substantial burden on children and their families. Real-time accurate prediction of child influenza epidemics can aid scientific and timely decision-making that may reduce the harm done to children infected with influenza. Several models have been proposed to predict influenza epidemics. However, most existing studies focus on adult influenza prediction. This study demonstrates the feasibility of using the LASSO (least absolute shrinkage and selection operator) model to predict influenza-like illness (ILI) levels in children between 2017 and 2020 in Shanghai, China. The performance of the LASSO model was compared with that of other statistical influenza-prediction techniques, including autoregressive integrated moving average (ARIMA), random forest (RF), ordinary least squares (OLS), and long short-term memory (LSTM). The LASSO model was observed to exhibit superior performance compared to the other candidate models. Owing to the variable shrinkage and low-variance properties of LASSO, it eliminated unimportant features and avoided overfitting. The experimental results suggest that the LASSO model can provide useful guidance for short-term child influenza prevention and control for schools, hospitals, and governments.
Effectiveness of Educational Intervention Based on Transtheoretical Model on Physical Activity and Menopausal Symptoms
Authors: Fallahipour Leila , Nazari Mahin , Karimi Masoud , Zare Elahe
Published: December 2022

Introduction. Menopause is an inevitable part of women’s lives. Physical activity as nonhormonal therapy can decrease the symptoms of menopause. This study is aimed at investigating the effect of educational intervention based on the transtheoretical model (TTM) on physical activity and menopausal symptoms of female clients of the health center in Pasargad City, Iran. Methods. This quasi‐experimental study was performed on 140 females admitted to health center of Pasargad City, Fars Province, Iran (intervention = 70 and control = 70). The data collection tool consisted of demographic data, menopause rating scale, international physical activities questionnaire, and TTM questionnaire (stages of change, processes of change, decision‐making balance, and self‐efficacy) that were completed before and two months after intervention. For intervention group, the educational program was implemented during 5 sessions of 50–55 min. Data were analyzed by SPSS 25 and by using Chi‐square test, independent t‐test, and paired t‐test. Results. After intervention, the mean scores of physical symptoms are sleep problems, muscle problems and discomfort, psychological symptoms, depression, irritability, and anxiety of intervention group decreased significantly post intervention (p < 0.001). Analysis showed that psychological symptoms, mental fatigue, somatic, and urogenital symptoms, and vaginal dryness increased 2 months after the intervention. Also, the mean score of cons, pros, decision balance, self‐efficacy, consciousness raising, dramatic relief, environmental reevaluation, and self‐reevaluation have significant changed in intervention group (p < 0.05). In addition, the top percent of progress can be seen in contemplation (31. 5%). Conclusion. This study showed the effectiveness of educational intervention based on TTM to reduce menopausal symptoms and promote physical activity in postmenopausal women.
Multiobjective Lightweight Optimization Design Method for a Dump Truck Carriage under Multiple Working Conditions
Authors: Zhang Kun , Zeng Jiabao , Zhang Qianxi , Pu Tonglin
Published: December 2022

To reduce the transportation cost and improve the fuel economy of a dump truck in road transport, vehicle lightweight optimization with the objectives such as the mass, stiffness, and sixth-order frequency of the carriage is adopted in this study. First, the carriage is divided into finite element meshes, and the working conditions of the carriage are analyzed under the conditions of full-load and uniform transportation, 0° lift, and 30° lift. Then, a comprehensive model consisting of full-load uniform transport and 0° lifting dual conditions is established, and 18 plate thicknesses are defined as design variables. The samples derived from the design variables of the carriages via the optimal Latin hypercube method are employed to analyze, in which the design variable that critically impacts the optimization objective is screened out from the sample for research. In addition, the dual-case approximation model constructed by a variety of methods is executed for accuracy comparison. And a moving least squares method combining linear and specific numerical values with the highest accuracy is selected to build a dual-case approximation model for the carriage. Ultimately, on the basis of the constructed double-condition approximation model, a multiobjective genetic algorithm is utilized to optimize the mass, bending stiffness, and sixth-order frequency. Compared with other methods, the multiobjective genetic algorithm can maintain the optimal solution, and the stored optimal solution can also be introduced into other groups to obtain another optimal solution. The simulation results, obtained from the scenarios of the carriage under the conditions of full-load uniform transportation, 0° lift and 30° lift, reveal that, on the basis of keeping the shape and structure of the original carriage unchanged, the mass is reduced by 1.215 t, the overall bending stiffness of the carriage is increased by 16300 N·mm−1, and the sixth-order modal frequency is optimized.
LiDAR-Based Windshear Detection via Statistical Features
Authors: Zhang Jie , Chan Pak Wai , Ng Michael K.
Published: December 2022

Windshear is a kind of microscale meteorological phenomenon which can cause danger to the landing and takeoff of aircrafts. Accurate windshear detection plays a crucial role in aviation safety. With the development of machine learning, several learning-based methods are proposed for windshear detection, i.e., windshear and non-windshear classification. To obtain accurate detection results, it is significant to extract features that can distinguish windshear and non-windshear properly from the obtained wind velocity data. In this paper, we mainly introduce two statistical indicators derived from the Doppler Light Detection and Ranging (LiDAR) observational wind velocity data by plan position illustrate (PPI) scans for windshear features construction. Besides the indicators directly derived from the wind velocity data, we also study the visual information from the corresponding conical images of wind velocity. Based on the proposed indicators, we construct three feature vectors for windshear and non-windshear classification. Inspired by the idea of multiple instance learning, the wind velocity data collected in the 4 minutes within the reported time spot are considered in the procedure of feature vector construction, which can reduce the possibility of windshear features missing. Both statistical methods and clustering methods are applied to evaluate the effectiveness of the proposed feature vectors. Numerical results show that the proposed feature vectors have good effect on windshear and non-windshear classification and can be used to provide more accurate windshear alerting to pilots in practice.
Performance Improvement of Multibiometric Authentication System Using Score Level Fusion with Ant Colony Optimization
Authors: Balraj E. , Abirami T.
Published: December 2022

Biometric systems are widely used by many organisations to protect the data from anomaly users. Unimodal biometric systems have many problems like noisy data, nonversatility, and nonuniversality. To avoid these problems, multibiometric system is the most suitable approach where we can integrate more than two individual modalities. Our proposed framework is utilised to minimize the rate of error while working on the exhibition by utilising the methodology of Ant Colony Optimization in view of Score Level Fusion strategies. The proposed work will extract the highlights from two distinct modalities of individual people like iris and face. The proposed frameworks employ ACO as an optimization technique to choose the fusion parameters called weight to apply the fusion rule for different biometric matcher used for Score Level Fusion mechanism. The matching scores will be calculated based on the fusion methods like sum, tanh, mean, median, min, max, and product. Our proposed system implements and analyzes four different types of fusion mechanisms.
Discovering Significant Sequential Patterns in Data Stream by an Efficient Two-Phase Procedure
Authors: Tang Huijun , Wang Le , Liu Yangguang , Qian Jiangbo
Published: December 2022

One essential topic of mining sequential patterns in the data stream is to optimize the time-space computations. However, more importantly, it should pay more attention to the significance of mining results as a large portion of them just response to the user-defined constraints purely by accident and they may have no statistical significance. In this paper, we propose FSSPDS, an efficient two-phase algorithm to discover the significant sequential patterns (SSPs) in the data stream with typical sliding windows, which has never been considered in existing problems. First, for generating SSPs candidates with high-quality, FSSPDS takes testable support and pattern length constraints into account and insignificant patterns were removed timely by a pattern-growth method. In the second phase, appropriate permutation testing is used to test the significance of the SSPs candidates. Exact permutation

p

values are obtained in a novel combination way based on unconditional Barnard’s test statistic which better reflects the process of data generations and collections. Experimental evaluations show that FSSPDS allows the discovery of SSPs in the data stream and rivals the state-of-the-art approaches efficiently under the control of family-wise error rate (FWER), especially for time efficiency, which was approximately an order of magnitude higher.
Analysis of Existence and Stability Results for Impulsive Fractional Integro-Differential Equations Involving the Atangana–Baleanu–Caputo Derivative under Integral Boundary Conditions
Authors: Reunsumrit Jiraporn , Karthikeyann Panjaiyan , Poornima Sadhasivam , Karthikeyan Kulandhaivel , Sitthiwirattham Thanin
Published: December 2022

In this study, we consider the existence results of solutions of impulsive Atangana–Baleanu–Caputo

A
B
C

fractional integro-differential equations with integral boundary conditions. Krasnoselskii’s fixed-point theorem and the Banach contraction principle are used to prove the existence and uniqueness of results. Moreover, we also establish Hyers–Ulam stability for this problem. An example is also presented at the end.
Pregnancy Risk Perception and Associated Factors among Pregnant Women Attending Antenatal Care at Health Centers in Jabi Tehnan District, Amhara, Northwestern Ethiopia, 2021
Authors: Alemu Demeke Andebet , Zegeye Ambaye Minayehu , Zeleke Liknaw Bewket , Dessie Wale Kumlachew , Melese Yilkal Dagnaw , Tarik Yaregal Desselaw , Zeleke Fentahun Tamene , Belay Dawit Misganaw , Siyoum Alemitu Ayele , Asfaha Berhane Teklay
Published: December 2022

Background. Pregnancy risk perception affects a pregnant woman’s decision about health care services such as prenatal care, place of birth, choices about medical interventions, adherence to medical procedures, and recommendations. Therefore, the study is aimed at assessing pregnancy risk perception and associated factors among pregnant women attending antenatal care at health centers in Jabi Tehnan District. Methods. An institutional-based cross-sectional study was conducted among 424 mothers attending ANC at health centers in the Jabi Tehnan District from April 1 to 30, 2021. Data was collected through a face-to-face interview using a structured questionnaire which was developed according to the health belief model. The logistic regression model was used using an adjusted odds ratio with 95% CI and

p

value
<
0.05

to declare significance and associations. Result. Four hundred twenty four (424) pregnant women were interviewed of which nearly half of the respondents 48% (43.2%, 52.7%) had good pregnancy risk perception. Women who had a history of obstetric complications (AOR: 95%

CI
=
3.44
:
1.73
,
6.83

), those who knew at least one pregnancy danger sign (AOR: 95%

CI
=
5.22
,
2.46
,
11.07

), pregnant women who had a bad obstetric history (AOR: 95%

CI
=
2.23
:
1.13
,
4.41

), and knowing women who died due to pregnancy-related complications (AOR: 95%

CI
=
2.85
:
1.45
,
5.60

) were more likely to have good perception towards pregnancy risk compared to their counterparts. Conclusion. Obstetric complications, awareness of pregnancy danger signs, bad obstetric history, and known women who died due to pregnancy-related complications were found to be significantly associated with pregnancy risk perception.
Comprehensive Assessment of Biomolecular Interactions of Morpholine‐Based Mixed Ligand Cu(II) and Zn(II) Complexes of 2,2′‐Bipyridine as Potential Anticancer and SARS‐CoV‐2 Agents: A Synergistic Experimental and Structure‐Based Virtual Screening
Authors: Sakthikumar Karunganathan , Krause Rui Werner Maçedo , Isamura Bienfait Kabuyaya
Published: December 2022

A new class of pharmacologically active mixed‐ligand complexes (1a‐2a) [MII(L)2 (bpy)], where L = 2‐(4‐morpholinobenzylideneamino)phenol), bpy = 2,2′‐bipyridine, MII = Cu (1a), and Zn (2a), were assigned an octahedral geometry by analytical and spectral measurements. Gel electrophoresis showed that complex (1a) demonstrated the complete DNA cleavage mediated by H2O2. The overall DNA‐binding constants observed from UV‐vis, fluorometric, hydrodynamic, and electrochemical titrations were in the following sequence: (1a) > (2a) > (HL), which suggests that the complexes might intercalate DNA, a possibility that is further supported by the biothermodynamic characteristics. The binding constant results of BSA by electronic absorption and fluorometric titration demonstrate that complex (1a) exhibits the highest binding effectiveness among others, which means that all compounds could interact with BSA through a static approach, additionally supported by FRET measurements. Density FunctionalTheory (DFT) and molecular docking calculations were relied on to unveil the electronic structure, reactivity, and interacting capability of all substances with DNA, BSA, and SARS‐CoV‐2 main protease (Mpro). These observed binding energies fell within the following ranges: −7.7 to −8.6, −7.2 to −10.2, and −6.7 to −8.2 kcal/mol, respectively. The higher reactivity of the complexes compared to free ligand is supported by the Frontier MolecularOrbital (FMO) theory. The in vitro antibacterial, cytotoxic, and radical scavenging characteristics revealed that complex (1a) has the best biological efficacy compared to others. This is encouraged because all experimental findings are closely correlated with the theoretical measurements.
Optimization of Antibacterial, Structures, and Thermal Properties of Alginate-ZrO2 Bionanocomposite by the Taguchi Method
Authors: Safaei Mohsen , Moradpoor Hedaiat , Salmani Mobarakeh Mohammad , Fallahnia Nima
Published: December 2022

Developing novel antibacterial chemicals is constantly necessary since bacterial resistance to antibiotics is an inevitable occurrence. This research aimed to find the ideal conditions for using antibacterial zirconia (ZrO2) NPs with polymer alginate nanocomposites. Using the Taguchi method, alginate biopolymer, zirconia NPs, and stirring time were utilized to construct nine nanocomposites. Analysis of Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible (UV-vis), spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM), and thermogravimetric analysis (TGA) indicated the development of nanocomposites with appropriate structural properties. Antibacterial efficacy against Streptococcus mutans (S. mutans) biofilm was the highest when the nanocomposite was formed under the circumstances of experiment 6 (zirconia 8 mg/ml, alginate 70 mg/ml, and 40 min stirring time). Alginate/zirconia bionanocomposites generated using the in situ technique proved efficient against S. mutans. Nanoparticles have a high surface-to-volume ratio and surface energy, which can cause them to agglomerate and make their antimicrobial effectiveness problematic. Using zirconia nanoparticles in an alginate polymer matrix in the form of nanocomposite can increase the stability of nanoparticles. Due to the advantageous antibacterial qualities of this bionanocomposite, it can be utilized in various medical materials and dental appliances.
Multiwinner Voting for Energy-Efficient Mobile Sink Rendezvous Selection in Wireless Sensor Network
Authors: Wu Xiaofeng , Chen Zhuangqi , Zhong Yi , Zhu Hui , Chen Xiao , Zhang Pingjian
Published: December 2022

Recent studies have demonstrated the advantage of applying mobile sink to prevent the energy-hole problem and prolong network lifetime in wireless sensor network. However, most researches treat the touring length constraint simply as the termination indicator of rendezvous point selection, which leads to a suboptimal solution. In this paper, we notice that the optimal set of rendezvous points is unknown but deterministic and propose to elect the set of rendezvous points directly with the multiwinner voting-based method instead of step-by-step selection. A weighted heuristic voter generation method is introduced to choose the representative voters, and a scoring rule is also well designed to obtain a satisfying solution. We also employ an iterative schema for the voting score update to refine the solution. We have conducted extensive experiments, and the results show that the proposed method can effectively prolong the network lifetime and achieve the competitive performance with other SOTA methods. Compared to the methods based on step-by-step selection, the proposed method increases the network lifetime by 23.2% and 10.5% on average under the balanced-distribution and unbalanced-distribution scenarios, respectively.
Diversity, Species Composition, and Relative Abundance of Avifauna at Debre Libanos Monastery, Ethiopia
Authors: Desalegn Tamenut , Negussie Fasika
Published: December 2022

Data on avifaunal diversity and distribution are vital to enhance and inform conservation efforts. Therefore, this study was conducted to explore the diversity, distribution, and relative abundance of bird species in the Derbe Libanos Monastery Forest. The data were collected from December 2019 to September 2020, covering both the wet and dry seasons. Natural forest, plantation, cliff forest, and settlement were identified as an important habitat for the birds using a stratified random sampling design based on vegetation composition and characteristics. Point counts were employed to identify and record birds in the four habitat types. During the study, 61 avian species belonging to 13 orders and 31 families were identified. The highest diversity (H′ = 3.43) and evenness (E = 0.96) were observed in the summer season in natural forests. The difference in abundance of bird species was statistically significant between observed and expected counts of each species in different habitats (χ2 = 629.97, df = 60, and

p
<
0.001

). Recognizing that the monastery forest has a large number of bird species, enhanced avian monitoring and forest reintegration opportunities should be prioritized for conservation.
Minimizing the Active Power Losses and Retaining the Voltage Profile of the Distribution System Using Soft Computing Techniques with DG Source
Authors: Sundararaman P. , Mohan E. , Kumer S. V. Aswin , Udayakumar Sridhar , Moti Abdissa Fekadu
Published: December 2022

The motivation of this research is to curtail the active power losses in the radial distribution system. This paper proposes a novel voltage stability indicator to determine the optimum conductor sizes for various distribution lines and find the conductor stability limit. This work proposes a new BAT algorithm for finding the optimal switching configurations using reconfiguration, which is used to minimize the active power losses. The proposed BAT algorithm gives the optimal locations to place the required amount of DG sources to improve the stability and minimize the power losses and maintain the voltage profile of the systems. The proposed BAT algorithm has been executed with the MATLAB 2016 software and compared with the differential evolution technique for IEEE 33 bus, IEEE 69 bus, and Indian real time 62 bus systems. The test results are applied on different conductors, and the real power flow on the different conductors are mapped in the proposed method using the novel voltage stability indicator. The radial distribution system has lower power losses, best voltage profile, cost of saving the DG source, optimal placing of a suitable rating of the DG source, optimal location of the DG source, and cost of saving the DG source which were achieved in this work. In this research, the distributed load flow analysis is implemented to find the parameters by the forward-backward sweep algorithm. The minimum bus voltage 0.95 pu is virtual in all the conductors. The loss reduction in the DE for IEEE 33 bus has been reduced from 42.4% to 45.3% and the loss reduction in IEEE 69 bus from 36.2% to 38.8% and the real time 62 bus from 47.5% to 49.15%. The loss reduction in the BAT algorithm for IEEE 33 bus has been reduced from 38.46% to 45.3% and the loss reduction in IEEE 69 bus is from 32.2% to 38.8%. The Indian standard real time 62 bus has been reduced from 38.92% to 49.15%. The proposed results are compared with the DE and BAT algorithm. The proposed BAT algorithm is found to be more effectual in reducing voltage deviation (VD) and reducing the power losses in the system.
The Prostate Stromal Transcriptome in Aggressive and Lethal Prostate Cancer
Authors: Ma Chaoran , Zhou Yinglu , Fanelli Giuseppe Nicolò , Stopsack Konrad H. , Fiorentino Michelangelo , Zadra Giorgia , Mucci Lorelei A. , Loda Massimo , Tyekucheva Svitlana , Penney Kathryn L.
Published: December 2022

Prostate cancer has a heterogeneous prognosis. Most previous studies have focused on the identification of prognostic biomarkers in the prostate cancer tumor. However, it is increasingly recognized that the tumor microenvironment contributes to prostate cancer aggressiveness and progression. We therefore examined whole transcriptome expression of the prostate stroma and associations with aggressive and lethal prostate cancer. We performed RNA sequencing (Illumina TruSeq Exome Capture) of 272 tumor-adjacent and 120 benign-adjacent macrodissected prostate stromal samples from 293 men with prostate cancer from the Health Professionals Follow-up Study and Physicians’ Health Study. We performed differential expression analysis comparing gene expression and pathways by Gleason score and lethal outcome. We also tested a previously developed stromal gene signature of Gleason score in these datasets. Comparing high- with low-Gleason score cancers, 26 genes (P < 0.001) and 12 pathways (FDR < 0.20) were significantly differentially expressed in tumor-adjacent stroma, including pathways related to stroma composition remodeling and DNA repair, with 73 genes and 65 pathways significant in benign-adjacent stroma. Comparing lethal with nonlethal prostate cancer, 11 genes were differentially expressed in tumor-adjacent and 15 genes in benign-adjacent stroma, and pathways involved in inflammatory response were differentially enriched in both tumor and benign-adjacent stroma. In addition, our previously identified Gleason stromal gene signature was validated to be associated with Gleason score in these data.

Implications: Our study uncovers stroma-specific genes and pathways that are differentially enriched with high Gleason score and lethal prostate cancer, demonstrating that the molecular investigation of the tumor microenvironment can provide additional information about prostate cancer prognosis.
Resolved Severe Primary Hypothyroidism in Sensenbrenner Syndrome Post Hepatorenal Transplantation: A Case Report
Authors: Al Noaim Khalid , Alfadhel Majid , Carré Aurore , Polak Michel , Al Mutair Angham
Published: December 2022

Introduction: Sensenbrenner syndrome, or cranioectodermal dysplasia (OMIM #218330), is a rare genetic condition inherited as an autosomal recessive with less than 70 reported cases worldwide. It results in multiorgan abnormalities along with ectodermal structural defects. No previous reported cases demonstrated primary hypothyroidism in a matter of Sensenbrenner syndrome. Case Presentation: Herein, we report a 6-year-old girl who suffered from progressive liver failure and end-stage renal disease secondary to Sensenbrenner syndrome, which was associated with severe primary hypothyroidism that completely recovered after a combined renal and liver transplant. Conclusion: For the first time in the literature, we report an association of Sensenbrenner syndrome with hypothyroidism that resolved after a combined renal and liver transplant. Such findings expand the clinical spectrum of this syndrome. However, a larger cohort is needed to confirm or exclude such an association. Our case highlights the importance of thyroid function monitoring in any patient with renal and liver failure prior to and after a hepatorenal transplant.
Combined Arginine and Insulin Stimulation Elicits a Robust and Consistent Copeptin Response in Short Children
Authors: March Christine A. , Sastry Shruti , McPhaul Michael J. , Wheeler Sarah E. , Garibaldi Luigi
Published: December 2022

Introduction: Copeptin, co-secreted with arginine vasopressin, is regulated by osmotic and volume stimuli but also responds to intravenous arginine and insulin-induced hypoglycemia. The serum copeptin response to the latter agents has been studied in adults but only to a limited extent in children. The objective of this study was to describe the copeptin response to combined arginine and insulin in children with normal posterior pituitary function. Methods: We conducted a prospective, single-arm assessment of serum copeptin concentrations in children (age 7–16 years, n = 38) undergoing growth hormone stimulation testing with an arginine-insulin tolerance test (AITT) for short stature or growth deceleration in a tertiary referral center. After overnight fasting, arginine (500 mg/kg) was administered between 0 and 30 min intravenously (IV) followed by insulin (0.1 units/kg IV) at 60 min. Copeptin serum concentrations were measured at baseline (0 min), at the post-arginine peak (60 min), and at the post-insulin peak (90 min; 30 min post-insulin), respectively. The main outcome was the peak copeptin concentration. Results: Mean ± SD copeptin concentrations increased from 9.9 ± 5.0 pmol/L at 0 min to 13.2 ± 5.8 pmol/L at 60 min (p < 0.0001 vs. 0 min) and 27.7 ± 14.2 pmol/L at 90 min (p < 0.0001 vs. 0 and 60 min). There was no significant correlation between copeptin concentrations and age, BMI, pubertal status, cortisol, growth hormone, or glucose concentrations. Discussion/Conclusion: Arginine and insulin appear to have an additive and consistent effect resulting in significant stimulation of copeptin secretion in children. The AITT may be a useful tool to evaluate for normal posterior pituitary function in this age-group, with potential implications for the evaluation of polyuria-polydipsia syndrome.
Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation
Authors: Eraifej John , Cabral Joana , Fernandes Henrique M. , Kahan Joshua , He Shenghong , Mancini Laura , Thornton John , White Mark , Yousry Tarek , Zrinzo Ludvic , Akram Harith , Limousin Patricia , Foltynie Tom , Aziz Tipu Z. , Deco Gustavo , Kringelbach Morten , Green Alexander L.
Published: December 2022

Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson’s disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson’s disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies.
Dynamic structure of motor cortical neuron coactivity carries behaviorally relevant information
Authors: Sundiang Marina , Hatsopoulos Nicholas G. , MacLean Jason N.
Published: December 2022

Skillful, voluntary movements are underpinned by computations performed by networks of interconnected neurons in the primary motor cortex (M1). Computations are reflected by patterns of coactivity between neurons. Using pairwise spike time statistics, coactivity can be summarized as a functional network (FN). Here, we show that the structure of FNs constructed from an instructed-delay reach task in nonhuman primates is behaviorally specific: Low-dimensional embedding and graph alignment scores show that FNs constructed from closer target reach directions are also closer in network space. Using short intervals across a trial, we constructed temporal FNs and found that temporal FNs traverse a low-dimensional subspace in a reach-specific trajectory. Alignment scores show that FNs become separable and correspondingly decodable shortly after the Instruction cue. Finally, we observe that reciprocal connections in FNs transiently decrease following the Instruction cue, consistent with the hypothesis that information external to the recorded population temporarily alters the structure of the network at this moment.
Paraphlomis strictiflora (Lamioideae, Lamiaceae), a new species from Guizhou, China
Authors: YUAN JING-CHEN , CHEN YA-PING , ZHAO YUE , LI HAI-BO , CHEN BIN , XIANG CHUN-LEI
Published: December 2022

As the largest genus within Paraphlomideae, the biodiversity of Paraphlomis remains to be explored. Here, P. strictiflora, a new species endemic to Fanjing Mountain in Guizhou Province, southwest China, is described and illustrated. Both our molecular phylogenetic analyses based on three plastid DNA markers (rpl32-trnL, rps16, and trnL-trnF) and nuclear ribosomal internal and external transcribed spacers (ITS and ETS) and morphological comparisons supported the treatment of P. strictiflora as a distinct species within Paraphlomis. Morphologically, P. strictiflora is most similar to P. lanceolata but can be distinguished by its much longer and conspicuously 5-veined calyx with triangular teeth, and white corolla with a straight lower lip.
Three new species of the tribe Grapholitini (Lepidoptera: Tortricidae: Olethreutinae) from India
Authors: REDDY KARTHIK M. , SHASHANK P. R.
Published: December 2022

Three new species of tribe Grapholitini (Lepidoptera: Tortricidae: Olethreutinae) from India viz., Acanthoclita bengaluruensis Reddy and Shashank, sp. nov., Grapholita constricta Reddy and Shashank sp. nov. and Thaumatotibia ramamurthyi Shashank and Reddy, sp. nov. are recorded. Descriptions and photographic illustrations of adult habitus and genitalia are provided.
Conducting Climate Change Risk Assessments for Companies: Lessons Learned
Authors: Teale Natalie , Quiring Steven M.
Published: December 2022

As the private sector becomes increasingly aware of the risks associated with climate change, climatologists have been engaging with companies to assess climate change risks and opportunities. Here, we outline how we have collaborated with a Fortune 500 company to assess the physical risks of climate change to their facilities. We provide a template for a climate change report card that we generated for >100 facilities globally. This report card is designed to communicate risk to company leadership and local facility managers. We believe that by sharing our experiences, climate scientists will be able to quantify and communicate climate risk more effectively to the private sector.
An Explanatory Multidimensional Random Item Effects Rating Scale Model
Authors: Huang Sijia , Luo Jinwen (Jevan) , Cai Li
Published: December 2022

Random item effects item response theory (IRT) models, which treat both person and item effects as random, have received much attention for more than a decade. The random item effects approach has several advantages in many practical settings. The present study introduced an explanatory multidimensional random item effects rating scale model. The proposed model was formulated under a novel parameterization of the nominal response model (NRM), and allows for flexible inclusion of person-related and item-related covariates (e.g., person characteristics and item features) to study their impacts on the person and item latent variables. A new variant of the Metropolis-Hastings Robbins-Monro (MH-RM) algorithm designed for latent variable models with crossed random effects was applied to obtain parameter estimates for the proposed model. A preliminary simulation study was conducted to evaluate the performance of the MH-RM algorithm for estimating the proposed model. Results indicated that the model parameters were well recovered. An empirical data set was analyzed to further illustrate the usage of the proposed model.
Gender differences in Syrian refugees in Jordan: Psychological, self-esteem, family function, marital satisfaction, and life satisfaction
Authors: Al-Krenawi Alean , Bell Melissa M
Published: December 2022

Aim:

The current study examined gender differences in mental health, self-esteem, family function, marital satisfaction, and life satisfaction between men and women living in a refugee camp for Syrian refugees in Jordan.

Method:

A snowball method used by local female and male students trained to collect data according to culturally competent methods. The following research instruments were deployed: Symptoms Checklist-SCL90, Self-esteem Scale, the McMaster Family Assessment Device, Marital Satisfaction Scale, and life Satisfaction Scale.

Results:

A sample of 290 adults (196 women and 94 men) living in a refugee camp in Jordan participated in the study. Findings revealed that marital satisfaction, self-esteem, and life satisfaction were significantly different between males and females, indicating less subjective well-being for women. Many of the mental health symptoms in this study were more common for women than men; particularly noteworthy were somatization, obsessive compulsive behavior, interpersonal sensitivity, depression, hostility, psychoticism, and higher scores on the Global Severity Index (GSI).

Conclusion:

While some stressors are not gender-specific, there are unique factors that women face which place them at increased risk of mental health problems. Implications for practice include a greater understanding of the challenges and resilience mechanisms that are related to gender and culture.