Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of CDT on Hemodynamics and Quality of Life in a Subgroup of Patients with Lower Limb Deep Vein Thrombosis Carel: A Case-Control Study

Objective To explore the effects of combined catheter-directed thrombolysis (CDT) on hemodynamics and quality of life in a subgroup of patients with lower limb deep vein thrombosis carel by using a case-control study. Methods Eighty-four patients with deep venous thrombosis (DVT: acute DVT and chronic DVT) of lower extremities treated in our hospital from April 2017 to June 2021 were randomly assigned into the control group (n = 42) and the research group (n = 42). The control group only received routine nursing combined with CDT; the research group was treated with cluster nursing l combined with CDT. The clinical efficacy, the difference in limb circumference, hemorheology, hemodynamics, coagulation index and life quality before and after treatment, and the nursing satisfaction scores were calculated. The effects of cluster nursing l combined with CDT on hemodynamics and life quality in patients with DVT of lower extremities were analyzed. Results The clinical curative effect of the research group was better than that of the control group (P < 0.05). After intervention, the difference in the thigh and leg perimeter in the research group was reduced, and the difference in the thigh and leg perimeter in the research group was significantly lower than that in the control group (P < 0.05). After intervention, the whole blood low shear viscosity, plasma viscosity, platelet aggregation rate, and fibrinogen in the research group were lower than those in the control group (P < 0.05). After intervention, segmental venous volume (SVC), maximum venous blood flow (MVO), and SVC/MVO in the research group were significantly higher than those before intervention, VRT was significantly prolonged, and MVO and venous pressure recovery time (VRT) were significantly higher than those in the control group. After intervention, D-dimer and fibrinogen decreased, prothrombin time and activated partial thromboplastin time increased in the research group, and the improvement of blood coagulation index in the research group was significantly better than that in the control group (P < 0.05). After intervention, the scores of quality of life in the research group decreased, and the scores of physiological function, psychological function, social function, and health self-cognition in the research group were lower than those in the control group (P < 0.05). The satisfaction of patients in the research group was significantly higher than that in the control group (P < 0.05). Conclusion The application of cluster nursing l combined with CDT can effectively prevent lower limb venous thrombosis after operation and can enhance patients' hemorheology, hemodynamics, and blood coagulation function and significantly promote their life quality, nursing satisfaction is high, and it is worth popularizing and applying in clinic.
Rate-Splitting Multiple Access for RIS-Aided Cell-Edge Users With Discrete Phase-Shifts

This letter investigates a reconfigurable intelligent surface (RIS)-aided multiple-input-single-output (MISO) communication system which uses rate-splitting multiple access (RSMA) protocol. A multi-antenna base-station (BS) communicates with $K$ cell-edge users using RSMA protocol. Each user is assisted with a dedicated RIS. The closed-form expression for the outage probability (OP) is derived considering the discrete and optimal phase-shifts introduced by RIS elements. The interdependent constraints of the threshold and the RSMA factors are derived and analyzed. For getting further insights, the expression for asymptotic OP is derived. Furthermore, the effects of various factors such as number of RIS elements, number of quantization bits, RSMA factors, threshold, etc. are discussed. The correctness of the derived expressions is validated using the Monte-Carlo simulations.
Performing (during) the Coronavirus Crisis: The Italian Populist Radical Right between National Opposition and Subnational Government

The first year of COVID-19 confirmed the standing of the populist radical right in Italy. While sitting in opposition at the national level, Giorgia Meloni's Brothers of Italy and Matteo Salvini's League shared common criticism of the Conte II government but experienced diverging trajectories in terms of popularity. The first had enjoyed growing support since the 2018 general election, whereas the second lost out after leaving the government coalition in 2019. These changes can be partly attributed to the different agency of their leaderships. Looking at the League's performance at the helm of key regions affected by the pandemic, moreover, its governors elaborated different responses to the crisis, which ostensibly reflect the varying allegiances and visions animating the internal life of the party. Overall and collectively considered, the Italian populist radical right broke even during the first year of COVID-19, but the crisis exposed the first cracks in Salvini's leadership.
Maximal Balanced Signed Biclique Enumeration in Signed Bipartite Graphs

Maximal biclique enumeration is a fundamental problem in bipartite graph analysis, and can find numerous applications. However, previous studies only focus on unsigned bipartite graphs. Signed information, such as friend and enemy, naturally exists in real-world networks. It is critical to leverage signed information to better characterize biclique. To fill this gap, in this paper, we propose a novel biclique model, named balanced signed biclique, by leveraging the property of balance theory. Specifically, given a signed bipartite graph $G$, two positive integers $\tau_{U}, \tau_{V}$, a subgraph $S=(U_{S},\ V_{S},\ E_{S})$ of $G$ is a balanced signed biclique if $i$) $S$ is a biclique without any unstable motif, i.e., unbalanced butterfly, and ii) $\vert U_{S}\vert \geq\tau_{U}$ and $\vert V_{S}\vert \geq\tau_{V}$. In this paper, we aim to enumerate all the maximal balanced signed bicliques, which is proved to be NP-hard. Moreover, due to the unique features of signed bipartite graphs, the previous works cannot be applied to our problem directly. To construct a reasonable baseline, we extend the existing biclique enumeration framework for unsigned bipartite graphs and integrate the developed balanced bipartite graph property. To scale for larger networks, novel optimized strategies are proposed to overcome the three limitations in the baseline method. Extensive experi-ments are conducted on 8 real-world datasets to demonstrate the efficiency and effectiveness of proposed techniques and model. Compared with the baseline approach, the optimized algorithm can achieve up to 3 orders of magnitude speedup.
HOTEL FRONT LINE EMPLOYEES’ PERCEPTIONS ON LEADERSHIP AND WORKPLACE MOTIVATION IN TIMES OF CRISIS

Purpose - This study aims to identify the extent to which different motivational elements can support strong bonds and good cooperation between front-line employees and hotels’ leadership in times of crisis and work suspension. Design - The views of a sample of employees working in 4 and 5 star hotels in Heraklion Prefecture were studied in May 2020, when hotel operations were suspended. Methodology - Two hundred and one completed questionnaires were collected, consisting of 31 six-point Likert scales, whose data were analysed using the Exploratory and Confirmatory Factor Analysis (CFA). Approach - The Exploratory Factor Analysis (EFA) followed the principal component method of extraction based on a varimax rotation, while the CFA adοpted the method of Structural Equation Modeling, that was based on the maximum likelihood method of estimation. Results - In times of crisis, front-line employees of hotels consider that the creation of strong bonds and a good spirit of cooperation and communication between them and the leadership of the hotels is strongly based on the exploitation of their skills and the developmental opportunities offered. Originality of the research - The research identified motivational factors that can support the creation of strong bonds and a good spirit of cooperation and communication between front-line employees and hotel management in times of crisis. On a practical level, the findings can help hotel managers gain strategic advantage and experience for the future, should they need to deal with similar situations.
Promoting well-being in the face of a pandemic: the role of sense of coherence and ego-resilience in the relationship between psychological distress and life satisfaction

COVID-19 has impacted negatively on the lives and academic activities of university students. This has contributed to increasing levels of psychological distress among this population group. Intrinsic and contextual factors can mediate the psychological impact of the pandemic. The study focuses on sense of coherence and ego-resilience as potential protective factors on indices of psychological distress and life satisfaction. Participants were undergraduate students (N = 337) at a South African university who completed six self-report questionnaires, namely, the Beck Hopelessness Scale, the University of California Los Angeles Loneliness Scale, the Center for Epidemiological Studies Depression Scale, the Sense of Coherence Scale, the Ego-Resilience Scale, and the Satisfaction with Life Scale. To examine the direct and mediating effects of sense of coherence and ego-resilience on psychological distress, structural equation modeling was used. Compared to previous research, greater psychological distress was found in the current sample. Moreover, while the hopelessness–life satisfaction relationship was only partially mediated by protective factors, the depression–life satisfaction relationship was fully mediated by sense of coherence and ego-resilience. The direct association between ego-resilience as well as sense of coherence and life satisfaction was significant, suggesting that these factors have a health-sustaining role.
Discovering meaningful engagement through interaction between customers and service robots

ABSTRACT Although service robots are causing a paradigm shift in the service industry by creating new interactions with customers, there is limited knowledge regarding which elements of service robots create desirable interactions with customers. To address this gap, this study invited situated action theory to investigate elements of service robots shaping customers’ meaningful engagement. 252 responses from the survey were analyzed. These revealed that some socio-functional elements are primary for meaningful engagement by affecting both experiential and instrumental outcomes, whereas others are salient for either one of the outcomes. Our analysis also examined personal innovativeness and viability of human–robot team pertaining to meaningful engagement. This study contributes to the literature by identifying socio-functional elements of service robots and exploring how they create meaningful engagement. It also provides practical implications to service companies, demonstrating critical elements of service robots for enhancing their service quality and for developing robot-driven service environments.
Efficient algorithm for approximating one-dimensional ground states

The density-matrix renormalization-group method is very effective at finding ground states of one-dimensional (1D) quantum systems in practice, but it is a heuristic method, and there is no known proof for when it works. In this article we describe an efficient classical algorithm which provably finds a good approximation of the ground state of 1D systems under well-defined conditions. More precisely, our algorithm finds a matrix product state of bond dimension D whose energy approximates the minimal energy such states can achieve. The running time is exponential in D, and so the algorithm can be considered tractable even for D, which is logarithmic in the size of the chain. The result also implies trivially that the ground state of any local commuting Hamiltonian in 1D can be approximated efficiently; we improve this to an exact algorithm.
Factors associated with poor treatment outcomes among tuberculosis patients in Kyangwali Refugee Settlement, Uganda, 2016–2017

Communicable diseases, alone or in combination with malnutrition, account for most deaths in complex emergencies including refugee settings. Tuberculosis and HIV/AIDS are increasingly becoming an important cause of morbidity and mortality in refugee settings. We described the treatment outcomes of TB patients and explored factors associated with treatment outcomes among TB patients attending two facilities in Kyangwali Refugee Settlement in Kikuube District, 2016–2017. We abstracted data on laboratory-confirmed patient data from TB registers from 2016 to 2017, in Kikuube Health Centre IV and Rwenyawawa Health Centre II, both located in Kyangwali Refugee Settlement. We abstracted data on socio-demographic variables including age and sex. Other variables were height, weight, final treatment outcomes, demographics, HIV status, TB treatment category, and history of TB. Treatment outcomes were categorized into favorable (including patients who were cured or those who completed treatment) and unfavorable (those in whom treatment failed, those who died, those lost to follow-up, or those not evaluated). We used logistic regression to identify factors associated with unfavorable treatment outcomes. We identified a total of 254 TB patients with a median age of 36 (IQR 26–48) years; 69% (175) were male and 54% (137) were refugees. The median weight was 50.4 kg (range 4–198). Overall, 139 (55%) had favorable outcomes while 115 (45%) had unfavorable outcomes. Refugees formed 53% (71) of those with favorable outcomes and 47% (63) of those with unfavorable outcomes 63(47%). We found that increasing age was statistically associated with unfavorable outcomes, while diagnosis with MDR-TB was associated with decreased odds for unfavorable treatment outcomes. The treatment success rate was lower compared to 85% recommended by WHO. However, the rates are similar to that reported by other studies in Uganda. Innovative approaches to improve treatment success rates with particular focus on persons aged 41–80 years should be devised.
Mixing Transactions with Arbitrary Values on Blockchains

Due to the transparency of blockchain, adversaries can observe the details of a transaction, and then utilize the amount as a unique quasi-identifier to make deanonymization. Nowadays, to obscure the linkages between receivers and senders within a transaction on the blockchain, mixing services are widely applied in many real applications to enhance cryptocurrencies' anonymity. The basic idea of mixing services is to hide an output within several other outputs in a transaction such that adversaries cannot distinguish them by their amounts since they are purposely selected to have the same amount. For a set of original outputs with different amounts, mixing services need to decompose them into a set of decomposed outputs, where any decomposed output has some other decomposed outputs with the same amount. Since the transaction fee is related to the number of outputs, we are motivated to decompose original outputs into a minimal set of decomposed outputs, which is challenging to guarantee the privacy-preserving effect at the same time. In this paper, we formally define the anonymity-aware output decomposition (AA-OD) problem, which aims to find a c-decomposition with a minimum number of decomposed outputs for a given original output set. A c-decomposition guarantees that for any original output $o$, there are at most $c$ of all decomposed outputs with an amount of $x$ coming from $o$. We prove that the AA-OD problem is NP-hard. Thus, we propose an approximation algorithm, namely Boggart11Boggart is a magical creature in J. K. Rowling's Harry Potter series who can shift his shape and no one knows what it looks like. , to solve the AA-OD problem with a (2/c + 3)-approximation bound on the number of decomposed outputs. We verify the efficiency and effectiveness of our approach through comprehensive experiments on both real and synthetic data sets.
Management of Sleep Disturbances in Parkinson’s Disease

Parkinson’s disease (PD) is defined by its motor symptoms rigidity, tremor, and akinesia. However, non-motor symptoms, particularly autonomic disorders and sleep disturbances, occur frequently in PD causing equivalent or even greater discomfort than motor symptoms effectively decreasing quality of life in patients and caregivers. Most common sleep disturbances in PD are insomnia, sleep disordered breathing, excessive daytime sleepiness, REM sleep behavior disorder, and sleep-related movement disorders such as restless legs syndrome. Despite their high prevalence, therapeutic options in the in- and outpatient setting are limited, partly due to lack of scientific evidence. The importance of sleep disturbances in neurodegenerative diseases has been further emphasized by recent evidence indicating a bidirectional relationship between neurodegeneration and sleep. A more profound insight into the underlying pathophysiological mechanisms intertwining sleep and neurodegeneration might lead to unique and individually tailored disease modifying or even neuroprotective therapeutic options in the long run. Therefore, current evidence concerning the management of sleep disturbances in PD will be discussed with the aim of providing a substantiated scaffolding for clinical decisions in long-term PD therapy.
Numerical methods for approximating solutions to rough differential equations

The main motivation behind writing this thesis was to construct numerical methods to approximate solutions to differential equations driven by rough paths, where the solution is considered in the rough path-sense. Rough paths of inhomogeneous degree of smoothness as driving noise are considered. We also aimed to find applications of these numerical methods to stochastic differential equations. After sketching the core ideas of the Rough Paths Theory in Chapter 1, the versions of the core theorems corresponding to the inhomogeneous degree of smoothness case are stated and proved in Chapter 2 along with some auxiliary claims on the continuity of the solution in a certain sense, including an RDE-version of Gronwall's lemma. In Chapter 3, numerical schemes for approximating solutions to differential equations driven by rough paths of inhomogeneous degree of smoothness are constructed. We start with setting up some principles of approximations. Then a general class of local approximations is introduced. This class is used to construct global approximations by pasting together the local ones. A general sufficient condition on the local approximations implying global convergence is given and proved. The next step is to construct particular local approximations in finite dimensions based on solutions to ordinary differential equations derived locally and satisfying the sufficient condition for global convergence. These local approximations require strong conditions on the one-form defining the rough differential equation. Finally, we show that when the local ODE-based schemes are applied in combination with rough polynomial approximations, the conditions on the one-form can be weakened. In Chapter 4, the results of Gyurko & Lyons (2010) on path-wise approximation of solutions to stochastic differential equations are recalled and extended to the truncated signature level of the solution. Furthermore, some practical considerations related to the implementation of high order schemes are described. The effectiveness of the derived schemes is demonstrated on numerical examples. In Chapter 5, the background theory of the Kusuoka-Lyons-Victoir (KLV) family of weak approximations is recalled and linked to the results of Chapter 4. We highlight how the different versions of the KLV family are related. Finally, a numerical evaluation of the autonomous ODE-based versions of the family is carried out, focusing on SDEs in dimensions up to 4, using cubature formulas of different degrees and several high order numerical ODE solvers. We demonstrate the effectiveness and the occasional non-effectiveness of the numerical approximations in cases when the KLV family is used in its original version and also when used in combination with partial sampling methods (Monte-Carlo, TBBA) and Romberg extrapolation.
Does a firm’s geographic feature matter for stock returns? Evidence from the Chinese A-share market

ABSTRACT This study reveals a new stock return predictability that relates to firms’ geographic features in the Chinese A-share market. Using a text-based measure of the degree of localness to capture the economic ties between firms and their provinces, we find that low-localized firms are slow to incorporate local information into stock prices. Specifically, there is a significant lead-lag effect in stock returns between high- and low-localized firms in the same region, and a portfolio that exploits this pattern can generate a monthly alpha of about 1%. This effect cannot be explained by geographic or industry return momentum, investors’ inattention, and limits to arbitrage. We find that this return predictability is mainly driven by investors’ limited information-processing capacity, and the evidence of predictability is stronger among low-localized firms with highly complicated business structures.
Promoting science process skills and learning outcomes through cybergogy approaches with PhET media for Junior High School Students

This study aims to describe the implementation of the cybergogy approach in improving Science Process Skills and learning outcomes. The research design used is One Group Pretest Posttest Design with a quantitative approach. The data collection method used is test and observation. The subjects of this study were 16 students of class VIII-A of Junior High School 2 Papar, Indonesia. Observers in this study were two science teachers and one student majoring in science. The instruments used in this study include learning implementation sheets, Science Process Skills observation sheets, pretest and posttest sheets of cognitive learning outcomes. The data analysis technique used quantitative analysis. Implementing learning through the cybergogy approach is carried out well, and a high learning success rate affects the improvement of science process skills and learning outcomes. The pretest of 80% and posttest of 94,4% showed increased cognitive and affective learning outcomes. The average N-Gain result obtained is 0.7 with high criteria. Science process skills as psychomotor and affective aspects experienced a significant increase. The use of PhET media also increased science process skills and learning outcomes. This study concludes that implementing the cybergogy approach to learning using PhET as a V-Lab media can improve science process skills and student learning outcomes.